diff --git a/pwiz/data/vendor_readers/ABI/ChromatogramList_ABI.cpp b/pwiz/data/vendor_readers/ABI/ChromatogramList_ABI.cpp
index 55bf2b9f0a..6d7652ee12 100644
--- a/pwiz/data/vendor_readers/ABI/ChromatogramList_ABI.cpp
+++ b/pwiz/data/vendor_readers/ABI/ChromatogramList_ABI.cpp
@@ -251,7 +251,8 @@ PWIZ_API_DECL ChromatogramPtr ChromatogramList_ABI::chromatogram(size_t index, D
             result->setTimeIntensityArrays(std::vector<double>(), std::vector<double>(), UO_minute, MS_number_of_detector_counts);
 
             pwiz::util::BinaryData<double> times, intensities;
-            experiment->getSIC(ie.transition, times, intensities);
+            bool ignoreScheduledLimitsForChromatograms = true;
+            experiment->getSIC(ie.transition, times, intensities, ignoreScheduledLimitsForChromatograms);
             result->defaultArrayLength = times.size();
 
             if (getBinaryData)
@@ -290,7 +291,8 @@ PWIZ_API_DECL ChromatogramPtr ChromatogramList_ABI::chromatogram(size_t index, D
             result->setTimeIntensityArrays(std::vector<double>(), std::vector<double>(), UO_minute, MS_number_of_detector_counts);
 
             pwiz::util::BinaryData<double> times, intensities;
-            experiment->getSIC(ie.transition, times, intensities);
+            bool ignoreScheduledLimitsForChromatograms = true;
+            experiment->getSIC(ie.transition, times, intensities, ignoreScheduledLimitsForChromatograms);
             result->defaultArrayLength = times.size();
 
             if (getBinaryData)
diff --git a/pwiz/utility/bindings/CLI/msdata/Reader.hpp b/pwiz/utility/bindings/CLI/msdata/Reader.hpp
index 2f69d3de7e..11f7dafeb9 100644
--- a/pwiz/utility/bindings/CLI/msdata/Reader.hpp
+++ b/pwiz/utility/bindings/CLI/msdata/Reader.hpp
@@ -67,52 +67,82 @@ public ref class ReaderConfig
 {
     public:
 
+    /// <summary>
     /// return Selected Ion Monitoring as spectra
+    /// </summary>
     bool simAsSpectra;
 
+    /// <summary>
     /// return Selected Reaction Monitoring as spectra
+    /// </summary>
     bool srmAsSpectra;
 
+    /// <summary>
 	/// when true, allows for skipping 0 length checks (and thus skip re-reading data for ABI)
+    /// </summary>
     bool acceptZeroLengthSpectra;
 
+    /// <summary>
     /// when true, allows certain vendor readers to produce profile data without zero intensity samples flanking each peak profile
+    /// </summary>
     bool ignoreZeroIntensityPoints;
 
+    /// <summary>
     /// when true, all drift bins/scans in a frame/block are written in combined form instead of as individual spectra
+    /// </summary>
     bool combineIonMobilitySpectra;
 
+    /// <summary>
     // when true, scans with only calibration data will be ignored (currently Waters lockmass only)
+    /// </summary>
     bool ignoreCalibrationScans;
 
+    /// <summary>
     /// when true, Waters SONAR data populates "drift" information with bin number instead of pseudo ion mobility values
+    /// </summary>
     bool reportSonarBins;
 
+    /// <summary>
     /// when true, if a reader cannot identify an instrument, an exception will be thrown asking users to report it
+    /// </summary>
     bool unknownInstrumentIsError;
 
+    /// <summary>
     /// when true, if a reader does not know what time zone was used to record a time, it will assume the time refers to the host's local time;
     /// when false, the reader will treat times with unknown time zone as UTC
+    /// </summary>
     bool adjustUnknownTimeZonesToHostTimeZone;
 
+    /// <summary>
     /// when nonzero, if reader can enumerate only spectra of ms level, it will (currently only supported by Bruker TDF)
+    /// </summary>
     int preferOnlyMsLevel;
 
+    /// <summary>
     /// when true, MS2 spectra without precursor/isolation information will be included in the output (currently only affects Bruker PASEF data)
+    /// </summary>
     bool allowMsMsWithoutPrecursor;
 
 
+    /// <summary>
     /// temporary(?) variable to avoid needing to regenerate Bruker test data
+    /// </summary>
     bool sortAndJitter;
 
+    /// <summary>
     /// when non-empty, only scans from precursors matching one of the included m/z and/or mobility windows will be enumerated; MS1 scans are affected only by the mobility filter
+    /// </summary>
     System::Collections::Generic::IList<MzMobilityWindow^>^ isolationMzAndMobilityFilter;
 
+    /// <summary>
     /// when true, global TIC and BPC chromatograms consist of only MS1 spectra (thus the number of time points cannot be assumed to be equal to the number of spectra)
+    /// </summary>
     bool globalChromatogramsAreMs1Only;
 
+    /// <summary>
     // When true, vendor-specific DDA processing is enabled. For Waters data, this involves combining MS2 scans which refer
     // to the same precursor from the same survey scan, and lockmass-correcting the precursor mass (if the lockmass refiner is active).
+    /// </summary>
     bool ddaProcessing;
 
     ReaderConfig()
diff --git a/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile.cpp b/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile.cpp
index 118873572f..559303242b 100644
--- a/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile.cpp
+++ b/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile.cpp
@@ -40,9 +40,11 @@
 #pragma managed
 #include "pwiz/utility/misc/cpp_cli_utilities.hpp"
 #include <msclr/auto_gcroot.h>
+#using <System.dll>
 #using <System.Xml.dll>
 using namespace pwiz::util;
 using namespace System;
+using namespace System::Text::RegularExpressions;
 using namespace Clearcore2::Data;
 using namespace Clearcore2::Data::AnalystDataProvider;
 using namespace Clearcore2::Data::Client;
@@ -128,9 +130,9 @@ struct ExperimentImpl : public Experiment
     virtual size_t getSRMSize() const;
     virtual void getSRM(size_t index, Target& target) const;
 
-    virtual void getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities) const;
+    virtual double getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities, bool ignoreScheduledLimits) const;
     virtual void getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities,
-                        double& basePeakX, double& basePeakY) const;
+                        double& basePeakX, double& basePeakY, bool ignoreScheduledLimits) const;
 
     virtual void getAcquisitionMassRange(double& startMz, double& stopMz) const;
     virtual ScanType getScanType() const;
@@ -147,6 +149,7 @@ struct ExperimentImpl : public Experiment
     const WiffFileImpl* wifffile_;
     gcroot<MSExperiment^> msExperiment;
     int sample, period, experiment;
+    bool hasHalfSizeRTWindow;
 
     ExperimentType experimentType;
     size_t simCount;
@@ -439,6 +442,27 @@ ExperimentImpl::ExperimentImpl(const WiffFileImpl* wifffile, int sample, int per
             transitionCount = msExperiment->Details->MassRangeInfo->Length;
         else if (experimentType == SIM)
             simCount = msExperiment->Details->MassRangeInfo->Length;
+
+        hasHalfSizeRTWindow = false;
+        try
+        {
+            auto softwareVersion = wifffile_->batch->GetSample(sample)->Details->SoftwareVersion;
+            auto sciexOsVersionRegex = gcnew Regex(R"(SCIEX OS (\d+)\.(\d+))");
+
+            auto match = sciexOsVersionRegex->Match(softwareVersion);
+            if (match->Success)
+            {
+                int major = Convert::ToInt32(match->Groups[1]->Value);
+                int minor = Convert::ToInt32(match->Groups[2]->Value);
+                hasHalfSizeRTWindow = !(major >= 3 && minor >= 1); // currently assumed present in SCIEX OS lower than v3.1
+                //if (hasHalfSizeRTWindow)
+                //    Console::Error->WriteLine("NOTE: data from " + softwareVersion + " has bugged half-width RTWindows");
+            }
+        }
+        catch (Exception^)
+        {
+            // ignore read past end of stream: no version details? probably acquired with Analyst?
+        }
     }
     CATCH_AND_FORWARD
 }
@@ -523,11 +547,12 @@ void ExperimentImpl::getSIM(size_t index, Target& target) const
 
         SIMMassRange^ transition = (SIMMassRange^) msExperiment->Details->MassRangeInfo[index];
 
+        double rtWindowMultiplier = hasHalfSizeRTWindow ? 1 : 0.5;
         target.type = TargetType_SIM;
         target.Q1 = transition->Mass;
         target.dwellTime = transition->DwellTime;
-        target.startTime = transition->ExpectedRT - transition->RTWindow / 2;
-        target.endTime = transition->ExpectedRT + transition->RTWindow / 2;
+        target.startTime = transition->ExpectedRT - transition->RTWindow * rtWindowMultiplier;
+        target.endTime = transition->ExpectedRT + transition->RTWindow * rtWindowMultiplier;
         target.compoundID = ToStdString(transition->Name);
         
         auto parameters = transition->CompoundDepParameters;
@@ -561,12 +586,13 @@ void ExperimentImpl::getSRM(size_t index, Target& target) const
 
         MRMMassRange^ transition = (MRMMassRange^) msExperiment->Details->MassRangeInfo[index];
 
+        double rtWindowMultiplier = hasHalfSizeRTWindow ? 1 : 0.5;
         target.type = TargetType_SRM;
         target.Q1 = transition->Q1Mass;
         target.Q3 = transition->Q3Mass;
         target.dwellTime = transition->DwellTime;
-        target.startTime = transition->ExpectedRT - transition->RTWindow;
-        target.endTime = transition->ExpectedRT + transition->RTWindow;
+        target.startTime = transition->ExpectedRT - transition->RTWindow * rtWindowMultiplier;
+        target.endTime = transition->ExpectedRT + transition->RTWindow * rtWindowMultiplier;
         target.compoundID = ToStdString(transition->Name);
 
         auto parameters = transition->CompoundDepParameters;
@@ -583,14 +609,30 @@ void ExperimentImpl::getSRM(size_t index, Target& target) const
     CATCH_AND_FORWARD
 }
 
-void ExperimentImpl::getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities) const
+double ExperimentImpl::getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities, bool ignoreScheduledLimits) const
 {
     try
     {
         if (index >= transitionCount+simCount)
-            throw std::out_of_range("[Experiment::getSIC()] index out of range");
+            throw std::out_of_range("[Experiment::getSIC()] index " + lexical_cast<string>(index) + " out of range");
+
+        Target target;
+        getSRM(index, target);
 
         ExtractedIonChromatogramSettings^ option = gcnew ExtractedIonChromatogramSettings(index);
+        if (ignoreScheduledLimits)
+        {
+            option->StartCycle = 0;
+            option->EndCycle = convertRetentionTimeToCycle(cycleTimes().back());
+            option->UseStartEndCycle = true;
+        }
+        else if (target.startTime != target.endTime)
+        {
+            option->StartCycle = convertRetentionTimeToCycle(target.startTime);
+            option->EndCycle = convertRetentionTimeToCycle(target.endTime);
+            option->UseStartEndCycle = true;
+        }
+
         ExtractedIonChromatogram^ xic = msExperiment->GetExtractedIonChromatogram(option);
 
         ToBinaryData(xic->GetActualXValues(), times);
@@ -600,20 +642,12 @@ void ExperimentImpl::getSIC(size_t index, pwiz::util::BinaryData<double>& times,
 }
 
 void ExperimentImpl::getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities,
-                            double& basePeakX, double& basePeakY) const
+                            double& basePeakX, double& basePeakY, bool ignoreScheduledLimits) const
 {
+    basePeakY = getSIC(index, times, intensities, ignoreScheduledLimits);
+
     try
     {
-        if (index >= transitionCount)
-            throw std::out_of_range("[Experiment::getSIC()] index " + lexical_cast<string>(index) + " out of range");
-
-        ExtractedIonChromatogramSettings^ option = gcnew ExtractedIonChromatogramSettings(index);
-        ExtractedIonChromatogram^ xic = msExperiment->GetExtractedIonChromatogram(option);
-
-        ToBinaryData(xic->GetActualXValues(), times);
-        ToBinaryData(xic->GetActualYValues(), intensities);
-
-        basePeakY = xic->MaximumYValue;
         basePeakX = 0;
         for (size_t i=0; i < intensities.size(); ++i)
             if (intensities[i] == basePeakY)
diff --git a/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile.hpp b/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile.hpp
index 2e6c301dbb..38103b57f5 100644
--- a/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile.hpp
+++ b/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile.hpp
@@ -190,9 +190,9 @@ struct PWIZ_API_DECL Experiment
 
     virtual size_t getSRMSize() const = 0;
     virtual void getSRM(size_t index, Target& target) const = 0;
-    virtual void getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities) const = 0;
+    virtual double getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities, bool ignoreScheduledLimits) const = 0;
     virtual void getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities,
-                        double& basePeakX, double& basePeakY) const = 0;
+                        double& basePeakX, double& basePeakY, bool ignoreScheduledLimits) const = 0;
 
     virtual void getAcquisitionMassRange(double& startMz, double& stopMz) const = 0;
     virtual ScanType getScanType() const = 0;
diff --git a/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile2.ipp b/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile2.ipp
index 3de57c4164..7cb9a45b8f 100644
--- a/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile2.ipp
+++ b/pwiz_aux/msrc/utility/vendor_api/ABI/WiffFile2.ipp
@@ -130,9 +130,9 @@ struct Experiment2Impl : public Experiment
     virtual size_t getSRMSize() const;
     virtual void getSRM(size_t index, Target& target) const;
 
-    virtual void getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities) const;
+    virtual double getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities, bool ignoreScheduledLimits) const;
     virtual void getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities,
-                        double& basePeakX, double& basePeakY) const;
+                        double& basePeakX, double& basePeakY, bool ignoreScheduledLimits) const;
 
     virtual void getAcquisitionMassRange(double& startMz, double& stopMz) const;
     virtual ScanType getScanType() const;
@@ -568,14 +568,15 @@ void Experiment2Impl::getSRM(size_t index, Target& target) const
     CATCH_AND_FORWARD
 }
 
-void Experiment2Impl::getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities) const
+double Experiment2Impl::getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities, bool ignoreScheduledLimits) const
 {
     double x, y;
-    getSIC(index, times, intensities, x, y);
+    getSIC(index, times, intensities, x, y, ignoreScheduledLimits);
+    return y;
 }
 
 void Experiment2Impl::getSIC(size_t index, pwiz::util::BinaryData<double>& times, pwiz::util::BinaryData<double>& intensities,
-                            double& basePeakX, double& basePeakY) const
+                            double& basePeakX, double& basePeakY, bool ignoreScheduledLimits) const
 {
     try
     {
diff --git a/pwiz_tools/Skyline/TestData/Results/AsymCEOptTest.cs b/pwiz_tools/Skyline/TestData/Results/AsymCEOptTest.cs
index 2769851db0..120521a704 100644
--- a/pwiz_tools/Skyline/TestData/Results/AsymCEOptTest.cs
+++ b/pwiz_tools/Skyline/TestData/Results/AsymCEOptTest.cs
@@ -64,7 +64,7 @@ private void ExportImport(ResultsTestDocumentContainer docContainer, string resu
             var chromSet = new ChromatogramSet("Optimize", new[] {resultsUri}, Annotations.EMPTY, optRegression);
             var measuredResults = new MeasuredResults(new[] { chromSet });
 
-            docContainer.ChangeMeasuredResults(measuredResults, 2, optSteps1 + optSteps2, 5*optSteps1 + 5*optSteps2);
+            docContainer.ChangeMeasuredResults(measuredResults, 2, optSteps1 + optSteps2, 86);
 
             // Check expected optimization data with missing values for steps below 10 volts CE
             int expectedMissingSteps = optSteps - optSteps1;
diff --git a/pwiz_tools/Skyline/TestTutorial/PeakPickingTutorialTest.cs b/pwiz_tools/Skyline/TestTutorial/PeakPickingTutorialTest.cs
index b6f569c9df..a37a426e74 100644
--- a/pwiz_tools/Skyline/TestTutorial/PeakPickingTutorialTest.cs
+++ b/pwiz_tools/Skyline/TestTutorial/PeakPickingTutorialTest.cs
@@ -96,7 +96,7 @@ private string GetTestPath(string relativePath)
 
         private readonly string[] EXPECTED_COEFFICIENTS =
         {
-            "-0.0783|-0.7492|2.2424|1.2062|0.0331|0.1515|0.1767| null |0.4983|6.3997|-0.0482|0.5476|0.6281| null | null | null | null | null ",
+            "-0.1095|-0.7689|1.9147|0.9647|0.0265|0.1822|0.2229| null |0.5529|6.5433|-0.0357|0.5285|0.6585| null | null | null | null | null ",
             "0.2900| null | null |5.9842|-0.0624|0.6681|0.7968| null | null | null | null | null | null | null | null | null | null | null ",
         };
 
@@ -193,7 +193,7 @@ protected override void DoTest()
             var editDlg = ShowDialog<EditPeakScoringModelDlg>(reintegrateDlg.AddPeakScoringModel);
             RunUI(() => editDlg.TrainModel());
             PauseForScreenShot<EditPeakScoringModelDlg.ModelTab>("Edit Peak Scoring Model form trained model", 6);
-            RunUI(() => Assert.AreEqual(0.5992, editDlg.PeakCalculatorsGrid.Items[3].PercentContribution ?? 0, 0.005));
+            RunUI(() => Assert.AreEqual(0.5893, editDlg.PeakCalculatorsGrid.Items[3].PercentContribution ?? 0, 0.005));
 
             RunUI(() => editDlg.SelectedGraphTab = 2);
             PauseForScreenShot<EditPeakScoringModelDlg.PvalueTab>("Edit Peak Scoring Model form p value graph metafile", 7);
diff --git a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/en/TestPeakPickingTutorial.log b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/en/TestPeakPickingTutorial.log
index db39e71c33..1c7e35eeb8 100644
--- a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/en/TestPeakPickingTutorial.log
+++ b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/en/TestPeakPickingTutorial.log
@@ -66,18 +66,18 @@ Summary   : Reintegrated peaks using "test1"
 All Info  :
 Reintegrated peaks using "test1"
 Reintegrate > Peak scoring model is "test1"
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0.078328345434545", Percentage Contribution = "-0.021" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0.74923684676032", Percentage Contribution = "0.066" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "2.24238344148558", Percentage Contribution = "0.081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "1.20618462186508", Percentage Contribution = "0.081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0.0330641179011537", Percentage Contribution = "-0.031" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0.151546153152723", Percentage Contribution = "0.05" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0.176740916361492", Percentage Contribution = "0.042" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0.498299821042048", Percentage Contribution = "0.02" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6.39974546904101", Percentage Contribution = "0.4" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0.0482245507469112", Percentage Contribution = "0.04" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0.547648429894388", Percentage Contribution = "0.1" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0.628130085182893", Percentage Contribution = "0.172" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0.10947638732718", Percentage Contribution = "-0.03" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0.768944834471997", Percentage Contribution = "0.067" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "1.91473647678043", Percentage Contribution = "0.071" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "0.964673347739591", Percentage Contribution = "0.064" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0.0265095737294209", Percentage Contribution = "-0.023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0.182160151225063", Percentage Contribution = "0.062" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0.222902489204878", Percentage Contribution = "0.053" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0.552867011319634", Percentage Contribution = "0.023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6.54328045047817", Percentage Contribution = "0.406" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0.035670415865123", Percentage Contribution = "0.028" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0.528458461601712", Percentage Contribution = "0.099" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0.658504481008043", Percentage Contribution = "0.181" }
 Reintegrate > Peak scoring model > Use decoys is True
 Reintegrate > Peak scoring model > Uses second best peaks is False
 Reintegrate > Integrate all peaks is True
@@ -88,63 +88,63 @@ Extra Info: Peak scoring model = "test1":
     [
         {
             Score Name = "Intensity",
-            Weight = "-0.078328345434545",
-            Percentage Contribution = "-0.021"
+            Weight = "-0.10947638732718",
+            Percentage Contribution = "-0.03"
         },
         {
             Score Name = "Retention time difference",
-            Weight = "-0.74923684676032",
-            Percentage Contribution = "0.066"
+            Weight = "-0.768944834471997",
+            Percentage Contribution = "0.067"
         },
         {
             Score Name = "Library intensity dot-product",
-            Weight = "2.24238344148558",
-            Percentage Contribution = "0.081"
+            Weight = "1.91473647678043",
+            Percentage Contribution = "0.071"
         },
         {
             Score Name = "Shape (weighted)",
-            Weight = "1.20618462186508",
-            Percentage Contribution = "0.081"
+            Weight = "0.964673347739591",
+            Percentage Contribution = "0.064"
         },
         {
             Score Name = "Co-elution (weighted)",
-            Weight = "0.0330641179011537",
-            Percentage Contribution = "-0.031"
+            Weight = "0.0265095737294209",
+            Percentage Contribution = "-0.023"
         },
         {
             Score Name = "Co-elution count",
-            Weight = "0.151546153152723",
-            Percentage Contribution = "0.05"
+            Weight = "0.182160151225063",
+            Percentage Contribution = "0.062"
         },
         {
             Score Name = "Signal to noise",
-            Weight = "0.176740916361492",
-            Percentage Contribution = "0.042"
+            Weight = "0.222902489204878",
+            Percentage Contribution = "0.053"
         },
         {
             Score Name = "Reference intensity dot-product",
-            Weight = "0.498299821042048",
-            Percentage Contribution = "0.02"
+            Weight = "0.552867011319634",
+            Percentage Contribution = "0.023"
         },
         {
             Score Name = "Reference shape (weighted)",
-            Weight = "6.39974546904101",
-            Percentage Contribution = "0.4"
+            Weight = "6.54328045047817",
+            Percentage Contribution = "0.406"
         },
         {
             Score Name = "Reference co-elution (weighted)",
-            Weight = "-0.0482245507469112",
-            Percentage Contribution = "0.04"
+            Weight = "-0.035670415865123",
+            Percentage Contribution = "0.028"
         },
         {
             Score Name = "Reference co-elution count",
-            Weight = "0.547648429894388",
-            Percentage Contribution = "0.1"
+            Weight = "0.528458461601712",
+            Percentage Contribution = "0.099"
         },
         {
             Score Name = "Standard Intensity",
-            Weight = "0.628130085182893",
-            Percentage Contribution = "0.172"
+            Weight = "0.658504481008043",
+            Percentage Contribution = "0.181"
         }
     ],
     Use decoys = True,
@@ -158,18 +158,18 @@ Summary   : Reintegrated peaks using "test1"
 All Info  :
 Reintegrated peaks using "test1"
 Reintegrate > Peak scoring model is "test1"
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0.078328345434545", Percentage Contribution = "-0.021" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0.74923684676032", Percentage Contribution = "0.066" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "2.24238344148558", Percentage Contribution = "0.081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "1.20618462186508", Percentage Contribution = "0.081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0.0330641179011537", Percentage Contribution = "-0.031" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0.151546153152723", Percentage Contribution = "0.05" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0.176740916361492", Percentage Contribution = "0.042" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0.498299821042048", Percentage Contribution = "0.02" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6.39974546904101", Percentage Contribution = "0.4" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0.0482245507469112", Percentage Contribution = "0.04" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0.547648429894388", Percentage Contribution = "0.1" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0.628130085182893", Percentage Contribution = "0.172" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0.10947638732718", Percentage Contribution = "-0.03" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0.768944834471997", Percentage Contribution = "0.067" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "1.91473647678043", Percentage Contribution = "0.071" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "0.964673347739591", Percentage Contribution = "0.064" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0.0265095737294209", Percentage Contribution = "-0.023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0.182160151225063", Percentage Contribution = "0.062" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0.222902489204878", Percentage Contribution = "0.053" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0.552867011319634", Percentage Contribution = "0.023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6.54328045047817", Percentage Contribution = "0.406" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0.035670415865123", Percentage Contribution = "0.028" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0.528458461601712", Percentage Contribution = "0.099" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0.658504481008043", Percentage Contribution = "0.181" }
 Reintegrate > Peak scoring model > Use decoys is True
 Reintegrate > Peak scoring model > Uses second best peaks is False
 Reintegrate > Only integrate significant q values is True
@@ -181,63 +181,63 @@ Extra Info: Peak scoring model = "test1":
     [
         {
             Score Name = "Intensity",
-            Weight = "-0.078328345434545",
-            Percentage Contribution = "-0.021"
+            Weight = "-0.10947638732718",
+            Percentage Contribution = "-0.03"
         },
         {
             Score Name = "Retention time difference",
-            Weight = "-0.74923684676032",
-            Percentage Contribution = "0.066"
+            Weight = "-0.768944834471997",
+            Percentage Contribution = "0.067"
         },
         {
             Score Name = "Library intensity dot-product",
-            Weight = "2.24238344148558",
-            Percentage Contribution = "0.081"
+            Weight = "1.91473647678043",
+            Percentage Contribution = "0.071"
         },
         {
             Score Name = "Shape (weighted)",
-            Weight = "1.20618462186508",
-            Percentage Contribution = "0.081"
+            Weight = "0.964673347739591",
+            Percentage Contribution = "0.064"
         },
         {
             Score Name = "Co-elution (weighted)",
-            Weight = "0.0330641179011537",
-            Percentage Contribution = "-0.031"
+            Weight = "0.0265095737294209",
+            Percentage Contribution = "-0.023"
         },
         {
             Score Name = "Co-elution count",
-            Weight = "0.151546153152723",
-            Percentage Contribution = "0.05"
+            Weight = "0.182160151225063",
+            Percentage Contribution = "0.062"
         },
         {
             Score Name = "Signal to noise",
-            Weight = "0.176740916361492",
-            Percentage Contribution = "0.042"
+            Weight = "0.222902489204878",
+            Percentage Contribution = "0.053"
         },
         {
             Score Name = "Reference intensity dot-product",
-            Weight = "0.498299821042048",
-            Percentage Contribution = "0.02"
+            Weight = "0.552867011319634",
+            Percentage Contribution = "0.023"
         },
         {
             Score Name = "Reference shape (weighted)",
-            Weight = "6.39974546904101",
-            Percentage Contribution = "0.4"
+            Weight = "6.54328045047817",
+            Percentage Contribution = "0.406"
         },
         {
             Score Name = "Reference co-elution (weighted)",
-            Weight = "-0.0482245507469112",
-            Percentage Contribution = "0.04"
+            Weight = "-0.035670415865123",
+            Percentage Contribution = "0.028"
         },
         {
             Score Name = "Reference co-elution count",
-            Weight = "0.547648429894388",
-            Percentage Contribution = "0.1"
+            Weight = "0.528458461601712",
+            Percentage Contribution = "0.099"
         },
         {
             Score Name = "Standard Intensity",
-            Weight = "0.628130085182893",
-            Percentage Contribution = "0.172"
+            Weight = "0.658504481008043",
+            Percentage Contribution = "0.181"
         }
     ],
     Use decoys = True,
diff --git a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/en/TestSrmTutorialLegacy.log b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/en/TestSrmTutorialLegacy.log
index 8300635062..47d90a5f6b 100644
--- a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/en/TestSrmTutorialLegacy.log
+++ b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/en/TestSrmTutorialLegacy.log
@@ -307,8 +307,8 @@ Summary   : Settings > Transition Settings changed
 All Info  :
 Transition Settings changed
 Settings > Transition Settings -- Prediction > Collision energy changed from "SCIEX" to "SRMcourse_20140211_Parameters_custom-CE-equation"
-Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "2", Slope = "0.0369", Intercept = "3.9361" }
-Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "3", Slope = "0.0208", Intercept = "9.0837" }
+Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "2", Slope = "0.025", Intercept = "8.6852" }
+Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "3", Slope = "0.046", Intercept = "-1.9754" }
 Settings > Transition Settings -- Instrument > Method match tolerance m/z changed from "0.055" to "0.01"
 
 Undo Redo : Managed results
diff --git a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/fr/TestPeakPickingTutorial.log b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/fr/TestPeakPickingTutorial.log
index 03bb4ca819..8f7bd0550f 100644
--- a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/fr/TestPeakPickingTutorial.log
+++ b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/fr/TestPeakPickingTutorial.log
@@ -66,18 +66,18 @@ Summary   : Reintegrated peaks using "test1"
 All Info  :
 Reintegrated peaks using "test1"
 Reintegrate > Peak scoring model is "test1"
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0,078328345434545", Percentage Contribution = "-0,021" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0,74923684676032", Percentage Contribution = "0,066" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "2,24238344148558", Percentage Contribution = "0,081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "1,20618462186508", Percentage Contribution = "0,081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0,0330641179011537", Percentage Contribution = "-0,031" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0,151546153152723", Percentage Contribution = "0,05" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0,176740916361492", Percentage Contribution = "0,042" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0,498299821042048", Percentage Contribution = "0,02" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6,39974546904101", Percentage Contribution = "0,4" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0,0482245507469112", Percentage Contribution = "0,04" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0,547648429894388", Percentage Contribution = "0,1" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0,628130085182893", Percentage Contribution = "0,172" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0,10947638732718", Percentage Contribution = "-0,03" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0,768944834471997", Percentage Contribution = "0,067" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "1,91473647678043", Percentage Contribution = "0,071" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "0,964673347739591", Percentage Contribution = "0,064" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0,0265095737294209", Percentage Contribution = "-0,023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0,182160151225063", Percentage Contribution = "0,062" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0,222902489204878", Percentage Contribution = "0,053" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0,552867011319634", Percentage Contribution = "0,023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6,54328045047817", Percentage Contribution = "0,406" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0,035670415865123", Percentage Contribution = "0,028" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0,528458461601712", Percentage Contribution = "0,099" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0,658504481008043", Percentage Contribution = "0,181" }
 Reintegrate > Peak scoring model > Use decoys is True
 Reintegrate > Peak scoring model > Uses second best peaks is False
 Reintegrate > Integrate all peaks is True
@@ -88,63 +88,63 @@ Extra Info: Peak scoring model = "test1":
     [
         {
             Score Name = "Intensity",
-            Weight = "-0,078328345434545",
-            Percentage Contribution = "-0,021"
+            Weight = "-0,10947638732718",
+            Percentage Contribution = "-0,03"
         },
         {
             Score Name = "Retention time difference",
-            Weight = "-0,74923684676032",
-            Percentage Contribution = "0,066"
+            Weight = "-0,768944834471997",
+            Percentage Contribution = "0,067"
         },
         {
             Score Name = "Library intensity dot-product",
-            Weight = "2,24238344148558",
-            Percentage Contribution = "0,081"
+            Weight = "1,91473647678043",
+            Percentage Contribution = "0,071"
         },
         {
             Score Name = "Shape (weighted)",
-            Weight = "1,20618462186508",
-            Percentage Contribution = "0,081"
+            Weight = "0,964673347739591",
+            Percentage Contribution = "0,064"
         },
         {
             Score Name = "Co-elution (weighted)",
-            Weight = "0,0330641179011537",
-            Percentage Contribution = "-0,031"
+            Weight = "0,0265095737294209",
+            Percentage Contribution = "-0,023"
         },
         {
             Score Name = "Co-elution count",
-            Weight = "0,151546153152723",
-            Percentage Contribution = "0,05"
+            Weight = "0,182160151225063",
+            Percentage Contribution = "0,062"
         },
         {
             Score Name = "Signal to noise",
-            Weight = "0,176740916361492",
-            Percentage Contribution = "0,042"
+            Weight = "0,222902489204878",
+            Percentage Contribution = "0,053"
         },
         {
             Score Name = "Reference intensity dot-product",
-            Weight = "0,498299821042048",
-            Percentage Contribution = "0,02"
+            Weight = "0,552867011319634",
+            Percentage Contribution = "0,023"
         },
         {
             Score Name = "Reference shape (weighted)",
-            Weight = "6,39974546904101",
-            Percentage Contribution = "0,4"
+            Weight = "6,54328045047817",
+            Percentage Contribution = "0,406"
         },
         {
             Score Name = "Reference co-elution (weighted)",
-            Weight = "-0,0482245507469112",
-            Percentage Contribution = "0,04"
+            Weight = "-0,035670415865123",
+            Percentage Contribution = "0,028"
         },
         {
             Score Name = "Reference co-elution count",
-            Weight = "0,547648429894388",
-            Percentage Contribution = "0,1"
+            Weight = "0,528458461601712",
+            Percentage Contribution = "0,099"
         },
         {
             Score Name = "Standard Intensity",
-            Weight = "0,628130085182893",
-            Percentage Contribution = "0,172"
+            Weight = "0,658504481008043",
+            Percentage Contribution = "0,181"
         }
     ],
     Use decoys = True,
@@ -158,18 +158,18 @@ Summary   : Reintegrated peaks using "test1"
 All Info  :
 Reintegrated peaks using "test1"
 Reintegrate > Peak scoring model is "test1"
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0,078328345434545", Percentage Contribution = "-0,021" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0,74923684676032", Percentage Contribution = "0,066" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "2,24238344148558", Percentage Contribution = "0,081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "1,20618462186508", Percentage Contribution = "0,081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0,0330641179011537", Percentage Contribution = "-0,031" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0,151546153152723", Percentage Contribution = "0,05" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0,176740916361492", Percentage Contribution = "0,042" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0,498299821042048", Percentage Contribution = "0,02" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6,39974546904101", Percentage Contribution = "0,4" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0,0482245507469112", Percentage Contribution = "0,04" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0,547648429894388", Percentage Contribution = "0,1" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0,628130085182893", Percentage Contribution = "0,172" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0,10947638732718", Percentage Contribution = "-0,03" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0,768944834471997", Percentage Contribution = "0,067" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "1,91473647678043", Percentage Contribution = "0,071" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "0,964673347739591", Percentage Contribution = "0,064" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0,0265095737294209", Percentage Contribution = "-0,023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0,182160151225063", Percentage Contribution = "0,062" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0,222902489204878", Percentage Contribution = "0,053" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0,552867011319634", Percentage Contribution = "0,023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6,54328045047817", Percentage Contribution = "0,406" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0,035670415865123", Percentage Contribution = "0,028" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0,528458461601712", Percentage Contribution = "0,099" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0,658504481008043", Percentage Contribution = "0,181" }
 Reintegrate > Peak scoring model > Use decoys is True
 Reintegrate > Peak scoring model > Uses second best peaks is False
 Reintegrate > Only integrate significant q values is True
@@ -181,63 +181,63 @@ Extra Info: Peak scoring model = "test1":
     [
         {
             Score Name = "Intensity",
-            Weight = "-0,078328345434545",
-            Percentage Contribution = "-0,021"
+            Weight = "-0,10947638732718",
+            Percentage Contribution = "-0,03"
         },
         {
             Score Name = "Retention time difference",
-            Weight = "-0,74923684676032",
-            Percentage Contribution = "0,066"
+            Weight = "-0,768944834471997",
+            Percentage Contribution = "0,067"
         },
         {
             Score Name = "Library intensity dot-product",
-            Weight = "2,24238344148558",
-            Percentage Contribution = "0,081"
+            Weight = "1,91473647678043",
+            Percentage Contribution = "0,071"
         },
         {
             Score Name = "Shape (weighted)",
-            Weight = "1,20618462186508",
-            Percentage Contribution = "0,081"
+            Weight = "0,964673347739591",
+            Percentage Contribution = "0,064"
         },
         {
             Score Name = "Co-elution (weighted)",
-            Weight = "0,0330641179011537",
-            Percentage Contribution = "-0,031"
+            Weight = "0,0265095737294209",
+            Percentage Contribution = "-0,023"
         },
         {
             Score Name = "Co-elution count",
-            Weight = "0,151546153152723",
-            Percentage Contribution = "0,05"
+            Weight = "0,182160151225063",
+            Percentage Contribution = "0,062"
         },
         {
             Score Name = "Signal to noise",
-            Weight = "0,176740916361492",
-            Percentage Contribution = "0,042"
+            Weight = "0,222902489204878",
+            Percentage Contribution = "0,053"
         },
         {
             Score Name = "Reference intensity dot-product",
-            Weight = "0,498299821042048",
-            Percentage Contribution = "0,02"
+            Weight = "0,552867011319634",
+            Percentage Contribution = "0,023"
         },
         {
             Score Name = "Reference shape (weighted)",
-            Weight = "6,39974546904101",
-            Percentage Contribution = "0,4"
+            Weight = "6,54328045047817",
+            Percentage Contribution = "0,406"
         },
         {
             Score Name = "Reference co-elution (weighted)",
-            Weight = "-0,0482245507469112",
-            Percentage Contribution = "0,04"
+            Weight = "-0,035670415865123",
+            Percentage Contribution = "0,028"
         },
         {
             Score Name = "Reference co-elution count",
-            Weight = "0,547648429894388",
-            Percentage Contribution = "0,1"
+            Weight = "0,528458461601712",
+            Percentage Contribution = "0,099"
         },
         {
             Score Name = "Standard Intensity",
-            Weight = "0,628130085182893",
-            Percentage Contribution = "0,172"
+            Weight = "0,658504481008043",
+            Percentage Contribution = "0,181"
         }
     ],
     Use decoys = True,
diff --git a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/fr/TestSrmTutorialLegacy.log b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/fr/TestSrmTutorialLegacy.log
index c74dfe788b..cbb9ed8797 100644
--- a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/fr/TestSrmTutorialLegacy.log
+++ b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/fr/TestSrmTutorialLegacy.log
@@ -307,8 +307,8 @@ Summary   : Settings > Transition Settings changed
 All Info  :
 Transition Settings changed
 Settings > Transition Settings -- Prediction > Collision energy changed from "SCIEX" to "SRMcourse_20140211_Parameters_custom-CE-equation"
-Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "2", Slope = "0,0369", Intercept = "3,9361" }
-Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "3", Slope = "0,0208", Intercept = "9,0837" }
+Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "2", Slope = "0,025", Intercept = "8,6852" }
+Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "3", Slope = "0,046", Intercept = "-1,9754" }
 Settings > Transition Settings -- Instrument > Method match tolerance m/z changed from "0,055" to "0,01"
 
 Undo Redo : Managed results
diff --git a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/ja/TestPeakPickingTutorial.log b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/ja/TestPeakPickingTutorial.log
index bb92e5f65a..5a8722adab 100644
--- a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/ja/TestPeakPickingTutorial.log
+++ b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/ja/TestPeakPickingTutorial.log
@@ -66,18 +66,18 @@ Summary   : 「test1」を使用してピークが再積分されました
 All Info  :
 「test1」を使用してピークが再積分されました
 再積分>ピークスコアモデルは"test1"です
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "強度", 加重 = "-0.078328345434545", 貢献度 = "-0.021" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "保持時間の差異", 加重 = "-0.74923684676032", 貢献度 = "0.066" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "ライブラリ強度内積", 加重 = "2.24238344148558", 貢献度 = "0.081" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "形（加重）", 加重 = "1.20618462186508", 貢献度 = "0.081" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "共溶出（加重）", 加重 = "0.0330641179011537", 貢献度 = "-0.031" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "共溶出数", 加重 = "0.151546153152723", 貢献度 = "0.05" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "信号対ノイズ比", 加重 = "0.176740916361492", 貢献度 = "0.042" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照強度内積", 加重 = "0.498299821042048", 貢献度 = "0.02" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照形（加重）", 加重 = "6.39974546904101", 貢献度 = "0.4" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照共溶出（加重）", 加重 = "-0.0482245507469112", 貢献度 = "0.04" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照共溶出数", 加重 = "0.547648429894388", 貢献度 = "0.1" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "標準強度", 加重 = "0.628130085182893", 貢献度 = "0.172" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "強度", 加重 = "-0.10947638732718", 貢献度 = "-0.03" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "保持時間の差異", 加重 = "-0.768944834471997", 貢献度 = "0.067" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "ライブラリ強度内積", 加重 = "1.91473647678043", 貢献度 = "0.071" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "形（加重）", 加重 = "0.964673347739591", 貢献度 = "0.064" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "共溶出（加重）", 加重 = "0.0265095737294209", 貢献度 = "-0.023" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "共溶出数", 加重 = "0.182160151225063", 貢献度 = "0.062" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "信号対ノイズ比", 加重 = "0.222902489204878", 貢献度 = "0.053" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照強度内積", 加重 = "0.552867011319634", 貢献度 = "0.023" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照形（加重）", 加重 = "6.54328045047817", 貢献度 = "0.406" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照共溶出（加重）", 加重 = "-0.035670415865123", 貢献度 = "0.028" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照共溶出数", 加重 = "0.528458461601712", 貢献度 = "0.099" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "標準強度", 加重 = "0.658504481008043", 貢献度 = "0.181" }が含まれています
 再積分>ピークスコアモデル>デコイを使用するは真です
 再積分>ピークスコアモデル>2番目に良いピークを使用は偽です
 再積分>すべてのピークを積分は真です
@@ -88,63 +88,63 @@ Extra Info: ピークスコアモデル = "test1":
     [
         {
             スコア名 = "強度",
-            加重 = "-0.078328345434545",
-            貢献度 = "-0.021"
+            加重 = "-0.10947638732718",
+            貢献度 = "-0.03"
         },
         {
             スコア名 = "保持時間の差異",
-            加重 = "-0.74923684676032",
-            貢献度 = "0.066"
+            加重 = "-0.768944834471997",
+            貢献度 = "0.067"
         },
         {
             スコア名 = "ライブラリ強度内積",
-            加重 = "2.24238344148558",
-            貢献度 = "0.081"
+            加重 = "1.91473647678043",
+            貢献度 = "0.071"
         },
         {
             スコア名 = "形（加重）",
-            加重 = "1.20618462186508",
-            貢献度 = "0.081"
+            加重 = "0.964673347739591",
+            貢献度 = "0.064"
         },
         {
             スコア名 = "共溶出（加重）",
-            加重 = "0.0330641179011537",
-            貢献度 = "-0.031"
+            加重 = "0.0265095737294209",
+            貢献度 = "-0.023"
         },
         {
             スコア名 = "共溶出数",
-            加重 = "0.151546153152723",
-            貢献度 = "0.05"
+            加重 = "0.182160151225063",
+            貢献度 = "0.062"
         },
         {
             スコア名 = "信号対ノイズ比",
-            加重 = "0.176740916361492",
-            貢献度 = "0.042"
+            加重 = "0.222902489204878",
+            貢献度 = "0.053"
         },
         {
             スコア名 = "参照強度内積",
-            加重 = "0.498299821042048",
-            貢献度 = "0.02"
+            加重 = "0.552867011319634",
+            貢献度 = "0.023"
         },
         {
             スコア名 = "参照形（加重）",
-            加重 = "6.39974546904101",
-            貢献度 = "0.4"
+            加重 = "6.54328045047817",
+            貢献度 = "0.406"
         },
         {
             スコア名 = "参照共溶出（加重）",
-            加重 = "-0.0482245507469112",
-            貢献度 = "0.04"
+            加重 = "-0.035670415865123",
+            貢献度 = "0.028"
         },
         {
             スコア名 = "参照共溶出数",
-            加重 = "0.547648429894388",
-            貢献度 = "0.1"
+            加重 = "0.528458461601712",
+            貢献度 = "0.099"
         },
         {
             スコア名 = "標準強度",
-            加重 = "0.628130085182893",
-            貢献度 = "0.172"
+            加重 = "0.658504481008043",
+            貢献度 = "0.181"
         }
     ],
     デコイを使用する = 真,
@@ -158,18 +158,18 @@ Summary   : 「test1」を使用してピークが再積分されました
 All Info  :
 「test1」を使用してピークが再積分されました
 再積分>ピークスコアモデルは"test1"です
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "強度", 加重 = "-0.078328345434545", 貢献度 = "-0.021" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "保持時間の差異", 加重 = "-0.74923684676032", 貢献度 = "0.066" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "ライブラリ強度内積", 加重 = "2.24238344148558", 貢献度 = "0.081" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "形（加重）", 加重 = "1.20618462186508", 貢献度 = "0.081" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "共溶出（加重）", 加重 = "0.0330641179011537", 貢献度 = "-0.031" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "共溶出数", 加重 = "0.151546153152723", 貢献度 = "0.05" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "信号対ノイズ比", 加重 = "0.176740916361492", 貢献度 = "0.042" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照強度内積", 加重 = "0.498299821042048", 貢献度 = "0.02" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照形（加重）", 加重 = "6.39974546904101", 貢献度 = "0.4" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照共溶出（加重）", 加重 = "-0.0482245507469112", 貢献度 = "0.04" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照共溶出数", 加重 = "0.547648429894388", 貢献度 = "0.1" }が含まれています
-再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "標準強度", 加重 = "0.628130085182893", 貢献度 = "0.172" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "強度", 加重 = "-0.10947638732718", 貢献度 = "-0.03" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "保持時間の差異", 加重 = "-0.768944834471997", 貢献度 = "0.067" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "ライブラリ強度内積", 加重 = "1.91473647678043", 貢献度 = "0.071" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "形（加重）", 加重 = "0.964673347739591", 貢献度 = "0.064" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "共溶出（加重）", 加重 = "0.0265095737294209", 貢献度 = "-0.023" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "共溶出数", 加重 = "0.182160151225063", 貢献度 = "0.062" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "信号対ノイズ比", 加重 = "0.222902489204878", 貢献度 = "0.053" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照強度内積", 加重 = "0.552867011319634", 貢献度 = "0.023" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照形（加重）", 加重 = "6.54328045047817", 貢献度 = "0.406" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照共溶出（加重）", 加重 = "-0.035670415865123", 貢献度 = "0.028" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "参照共溶出数", 加重 = "0.528458461601712", 貢献度 = "0.099" }が含まれています
+再積分>ピークスコアモデル>フィーチャースコア：{ スコア名 = "標準強度", 加重 = "0.658504481008043", 貢献度 = "0.181" }が含まれています
 再積分>ピークスコアモデル>デコイを使用するは真です
 再積分>ピークスコアモデル>2番目に良いピークを使用は偽です
 再積分>有意なQ値のみを積分は真です
@@ -181,63 +181,63 @@ Extra Info: ピークスコアモデル = "test1":
     [
         {
             スコア名 = "強度",
-            加重 = "-0.078328345434545",
-            貢献度 = "-0.021"
+            加重 = "-0.10947638732718",
+            貢献度 = "-0.03"
         },
         {
             スコア名 = "保持時間の差異",
-            加重 = "-0.74923684676032",
-            貢献度 = "0.066"
+            加重 = "-0.768944834471997",
+            貢献度 = "0.067"
         },
         {
             スコア名 = "ライブラリ強度内積",
-            加重 = "2.24238344148558",
-            貢献度 = "0.081"
+            加重 = "1.91473647678043",
+            貢献度 = "0.071"
         },
         {
             スコア名 = "形（加重）",
-            加重 = "1.20618462186508",
-            貢献度 = "0.081"
+            加重 = "0.964673347739591",
+            貢献度 = "0.064"
         },
         {
             スコア名 = "共溶出（加重）",
-            加重 = "0.0330641179011537",
-            貢献度 = "-0.031"
+            加重 = "0.0265095737294209",
+            貢献度 = "-0.023"
         },
         {
             スコア名 = "共溶出数",
-            加重 = "0.151546153152723",
-            貢献度 = "0.05"
+            加重 = "0.182160151225063",
+            貢献度 = "0.062"
         },
         {
             スコア名 = "信号対ノイズ比",
-            加重 = "0.176740916361492",
-            貢献度 = "0.042"
+            加重 = "0.222902489204878",
+            貢献度 = "0.053"
         },
         {
             スコア名 = "参照強度内積",
-            加重 = "0.498299821042048",
-            貢献度 = "0.02"
+            加重 = "0.552867011319634",
+            貢献度 = "0.023"
         },
         {
             スコア名 = "参照形（加重）",
-            加重 = "6.39974546904101",
-            貢献度 = "0.4"
+            加重 = "6.54328045047817",
+            貢献度 = "0.406"
         },
         {
             スコア名 = "参照共溶出（加重）",
-            加重 = "-0.0482245507469112",
-            貢献度 = "0.04"
+            加重 = "-0.035670415865123",
+            貢献度 = "0.028"
         },
         {
             スコア名 = "参照共溶出数",
-            加重 = "0.547648429894388",
-            貢献度 = "0.1"
+            加重 = "0.528458461601712",
+            貢献度 = "0.099"
         },
         {
             スコア名 = "標準強度",
-            加重 = "0.628130085182893",
-            貢献度 = "0.172"
+            加重 = "0.658504481008043",
+            貢献度 = "0.181"
         }
     ],
     デコイを使用する = 真,
diff --git a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/ja/TestSrmTutorialLegacy.log b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/ja/TestSrmTutorialLegacy.log
index b7d3bbea13..b7caba5f7d 100644
--- a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/ja/TestSrmTutorialLegacy.log
+++ b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/ja/TestSrmTutorialLegacy.log
@@ -307,8 +307,8 @@ Summary   : 設定>トランジションの設定が変更されました
 All Info  :
 トランジションの設定が変更されました
 設定>トランジションの設定－予測>衝突エネルギーは"SCIEX"から"SRMcourse_20140211_Parameters_custom-CE-equation"に変更されました
-設定>トランジションの設定－予測>衝突エネルギー>回帰パラメータ：{ 電荷 = "2", 傾き = "0.0369", 切片 = "3.9361" }が含まれています
-設定>トランジションの設定－予測>衝突エネルギー>回帰パラメータ：{ 電荷 = "3", 傾き = "0.0208", 切片 = "9.0837" }が含まれています
+設定>トランジションの設定－予測>衝突エネルギー>回帰パラメータ：{ 電荷 = "2", 傾き = "0.025", 切片 = "8.6852" }が含まれています
+設定>トランジションの設定－予測>衝突エネルギー>回帰パラメータ：{ 電荷 = "3", 傾き = "0.046", 切片 = "-1.9754" }が含まれています
 設定>トランジションの設定－装置>メソッド許容誤差m/zは"0.055"から"0.01"に変更されました
 
 Undo Redo : 結果が管理されました
diff --git a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/tr/TestPeakPickingTutorial.log b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/tr/TestPeakPickingTutorial.log
index 03bb4ca819..8f7bd0550f 100644
--- a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/tr/TestPeakPickingTutorial.log
+++ b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/tr/TestPeakPickingTutorial.log
@@ -66,18 +66,18 @@ Summary   : Reintegrated peaks using "test1"
 All Info  :
 Reintegrated peaks using "test1"
 Reintegrate > Peak scoring model is "test1"
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0,078328345434545", Percentage Contribution = "-0,021" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0,74923684676032", Percentage Contribution = "0,066" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "2,24238344148558", Percentage Contribution = "0,081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "1,20618462186508", Percentage Contribution = "0,081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0,0330641179011537", Percentage Contribution = "-0,031" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0,151546153152723", Percentage Contribution = "0,05" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0,176740916361492", Percentage Contribution = "0,042" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0,498299821042048", Percentage Contribution = "0,02" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6,39974546904101", Percentage Contribution = "0,4" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0,0482245507469112", Percentage Contribution = "0,04" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0,547648429894388", Percentage Contribution = "0,1" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0,628130085182893", Percentage Contribution = "0,172" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0,10947638732718", Percentage Contribution = "-0,03" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0,768944834471997", Percentage Contribution = "0,067" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "1,91473647678043", Percentage Contribution = "0,071" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "0,964673347739591", Percentage Contribution = "0,064" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0,0265095737294209", Percentage Contribution = "-0,023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0,182160151225063", Percentage Contribution = "0,062" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0,222902489204878", Percentage Contribution = "0,053" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0,552867011319634", Percentage Contribution = "0,023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6,54328045047817", Percentage Contribution = "0,406" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0,035670415865123", Percentage Contribution = "0,028" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0,528458461601712", Percentage Contribution = "0,099" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0,658504481008043", Percentage Contribution = "0,181" }
 Reintegrate > Peak scoring model > Use decoys is True
 Reintegrate > Peak scoring model > Uses second best peaks is False
 Reintegrate > Integrate all peaks is True
@@ -88,63 +88,63 @@ Extra Info: Peak scoring model = "test1":
     [
         {
             Score Name = "Intensity",
-            Weight = "-0,078328345434545",
-            Percentage Contribution = "-0,021"
+            Weight = "-0,10947638732718",
+            Percentage Contribution = "-0,03"
         },
         {
             Score Name = "Retention time difference",
-            Weight = "-0,74923684676032",
-            Percentage Contribution = "0,066"
+            Weight = "-0,768944834471997",
+            Percentage Contribution = "0,067"
         },
         {
             Score Name = "Library intensity dot-product",
-            Weight = "2,24238344148558",
-            Percentage Contribution = "0,081"
+            Weight = "1,91473647678043",
+            Percentage Contribution = "0,071"
         },
         {
             Score Name = "Shape (weighted)",
-            Weight = "1,20618462186508",
-            Percentage Contribution = "0,081"
+            Weight = "0,964673347739591",
+            Percentage Contribution = "0,064"
         },
         {
             Score Name = "Co-elution (weighted)",
-            Weight = "0,0330641179011537",
-            Percentage Contribution = "-0,031"
+            Weight = "0,0265095737294209",
+            Percentage Contribution = "-0,023"
         },
         {
             Score Name = "Co-elution count",
-            Weight = "0,151546153152723",
-            Percentage Contribution = "0,05"
+            Weight = "0,182160151225063",
+            Percentage Contribution = "0,062"
         },
         {
             Score Name = "Signal to noise",
-            Weight = "0,176740916361492",
-            Percentage Contribution = "0,042"
+            Weight = "0,222902489204878",
+            Percentage Contribution = "0,053"
         },
         {
             Score Name = "Reference intensity dot-product",
-            Weight = "0,498299821042048",
-            Percentage Contribution = "0,02"
+            Weight = "0,552867011319634",
+            Percentage Contribution = "0,023"
         },
         {
             Score Name = "Reference shape (weighted)",
-            Weight = "6,39974546904101",
-            Percentage Contribution = "0,4"
+            Weight = "6,54328045047817",
+            Percentage Contribution = "0,406"
         },
         {
             Score Name = "Reference co-elution (weighted)",
-            Weight = "-0,0482245507469112",
-            Percentage Contribution = "0,04"
+            Weight = "-0,035670415865123",
+            Percentage Contribution = "0,028"
         },
         {
             Score Name = "Reference co-elution count",
-            Weight = "0,547648429894388",
-            Percentage Contribution = "0,1"
+            Weight = "0,528458461601712",
+            Percentage Contribution = "0,099"
         },
         {
             Score Name = "Standard Intensity",
-            Weight = "0,628130085182893",
-            Percentage Contribution = "0,172"
+            Weight = "0,658504481008043",
+            Percentage Contribution = "0,181"
         }
     ],
     Use decoys = True,
@@ -158,18 +158,18 @@ Summary   : Reintegrated peaks using "test1"
 All Info  :
 Reintegrated peaks using "test1"
 Reintegrate > Peak scoring model is "test1"
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0,078328345434545", Percentage Contribution = "-0,021" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0,74923684676032", Percentage Contribution = "0,066" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "2,24238344148558", Percentage Contribution = "0,081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "1,20618462186508", Percentage Contribution = "0,081" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0,0330641179011537", Percentage Contribution = "-0,031" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0,151546153152723", Percentage Contribution = "0,05" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0,176740916361492", Percentage Contribution = "0,042" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0,498299821042048", Percentage Contribution = "0,02" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6,39974546904101", Percentage Contribution = "0,4" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0,0482245507469112", Percentage Contribution = "0,04" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0,547648429894388", Percentage Contribution = "0,1" }
-Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0,628130085182893", Percentage Contribution = "0,172" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Intensity", Weight = "-0,10947638732718", Percentage Contribution = "-0,03" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Retention time difference", Weight = "-0,768944834471997", Percentage Contribution = "0,067" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Library intensity dot-product", Weight = "1,91473647678043", Percentage Contribution = "0,071" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Shape (weighted)", Weight = "0,964673347739591", Percentage Contribution = "0,064" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution (weighted)", Weight = "0,0265095737294209", Percentage Contribution = "-0,023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Co-elution count", Weight = "0,182160151225063", Percentage Contribution = "0,062" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Signal to noise", Weight = "0,222902489204878", Percentage Contribution = "0,053" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference intensity dot-product", Weight = "0,552867011319634", Percentage Contribution = "0,023" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference shape (weighted)", Weight = "6,54328045047817", Percentage Contribution = "0,406" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution (weighted)", Weight = "-0,035670415865123", Percentage Contribution = "0,028" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Reference co-elution count", Weight = "0,528458461601712", Percentage Contribution = "0,099" }
+Reintegrate > Peak scoring model > Feature scores : contains { Score Name = "Standard Intensity", Weight = "0,658504481008043", Percentage Contribution = "0,181" }
 Reintegrate > Peak scoring model > Use decoys is True
 Reintegrate > Peak scoring model > Uses second best peaks is False
 Reintegrate > Only integrate significant q values is True
@@ -181,63 +181,63 @@ Extra Info: Peak scoring model = "test1":
     [
         {
             Score Name = "Intensity",
-            Weight = "-0,078328345434545",
-            Percentage Contribution = "-0,021"
+            Weight = "-0,10947638732718",
+            Percentage Contribution = "-0,03"
         },
         {
             Score Name = "Retention time difference",
-            Weight = "-0,74923684676032",
-            Percentage Contribution = "0,066"
+            Weight = "-0,768944834471997",
+            Percentage Contribution = "0,067"
         },
         {
             Score Name = "Library intensity dot-product",
-            Weight = "2,24238344148558",
-            Percentage Contribution = "0,081"
+            Weight = "1,91473647678043",
+            Percentage Contribution = "0,071"
         },
         {
             Score Name = "Shape (weighted)",
-            Weight = "1,20618462186508",
-            Percentage Contribution = "0,081"
+            Weight = "0,964673347739591",
+            Percentage Contribution = "0,064"
         },
         {
             Score Name = "Co-elution (weighted)",
-            Weight = "0,0330641179011537",
-            Percentage Contribution = "-0,031"
+            Weight = "0,0265095737294209",
+            Percentage Contribution = "-0,023"
         },
         {
             Score Name = "Co-elution count",
-            Weight = "0,151546153152723",
-            Percentage Contribution = "0,05"
+            Weight = "0,182160151225063",
+            Percentage Contribution = "0,062"
         },
         {
             Score Name = "Signal to noise",
-            Weight = "0,176740916361492",
-            Percentage Contribution = "0,042"
+            Weight = "0,222902489204878",
+            Percentage Contribution = "0,053"
         },
         {
             Score Name = "Reference intensity dot-product",
-            Weight = "0,498299821042048",
-            Percentage Contribution = "0,02"
+            Weight = "0,552867011319634",
+            Percentage Contribution = "0,023"
         },
         {
             Score Name = "Reference shape (weighted)",
-            Weight = "6,39974546904101",
-            Percentage Contribution = "0,4"
+            Weight = "6,54328045047817",
+            Percentage Contribution = "0,406"
         },
         {
             Score Name = "Reference co-elution (weighted)",
-            Weight = "-0,0482245507469112",
-            Percentage Contribution = "0,04"
+            Weight = "-0,035670415865123",
+            Percentage Contribution = "0,028"
         },
         {
             Score Name = "Reference co-elution count",
-            Weight = "0,547648429894388",
-            Percentage Contribution = "0,1"
+            Weight = "0,528458461601712",
+            Percentage Contribution = "0,099"
         },
         {
             Score Name = "Standard Intensity",
-            Weight = "0,628130085182893",
-            Percentage Contribution = "0,172"
+            Weight = "0,658504481008043",
+            Percentage Contribution = "0,181"
         }
     ],
     Use decoys = True,
diff --git a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/tr/TestSrmTutorialLegacy.log b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/tr/TestSrmTutorialLegacy.log
index c74dfe788b..cbb9ed8797 100644
--- a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/tr/TestSrmTutorialLegacy.log
+++ b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/tr/TestSrmTutorialLegacy.log
@@ -307,8 +307,8 @@ Summary   : Settings > Transition Settings changed
 All Info  :
 Transition Settings changed
 Settings > Transition Settings -- Prediction > Collision energy changed from "SCIEX" to "SRMcourse_20140211_Parameters_custom-CE-equation"
-Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "2", Slope = "0,0369", Intercept = "3,9361" }
-Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "3", Slope = "0,0208", Intercept = "9,0837" }
+Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "2", Slope = "0,025", Intercept = "8,6852" }
+Settings > Transition Settings -- Prediction > Collision energy > Regression parameters : contains { Charge = "3", Slope = "0,046", Intercept = "-1,9754" }
 Settings > Transition Settings -- Instrument > Method match tolerance m/z changed from "0,055" to "0,01"
 
 Undo Redo : Managed results
diff --git a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/zh/TestPeakPickingTutorial.log b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/zh/TestPeakPickingTutorial.log
index d1967ceef5..2c24d60fbd 100644
--- a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/zh/TestPeakPickingTutorial.log
+++ b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/zh/TestPeakPickingTutorial.log
@@ -66,18 +66,18 @@ Summary   : 已使用“test1”重新合并峰
 All Info  :
 已使用“test1”重新合并峰
 重新合并 > 峰得分模型 是 "test1"
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "强度", 权重 = "-0.078328345434545", 贡献百分比 = "-0.021" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "保留时间差异", 权重 = "-0.74923684676032", 贡献百分比 = "0.066" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "库强度点积", 权重 = "2.24238344148558", 贡献百分比 = "0.081" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "形状（权重）", 权重 = "1.20618462186508", 贡献百分比 = "0.081" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "共洗脱（权重）", 权重 = "0.0330641179011537", 贡献百分比 = "-0.031" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "共洗脱计数", 权重 = "0.151546153152723", 贡献百分比 = "0.05" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "噪声信号", 权重 = "0.176740916361492", 贡献百分比 = "0.042" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考强度点积", 权重 = "0.498299821042048", 贡献百分比 = "0.02" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考形状（权重）", 权重 = "6.39974546904101", 贡献百分比 = "0.4" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考共洗脱（权重）", 权重 = "-0.0482245507469112", 贡献百分比 = "0.04" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考共洗脱计数", 权重 = "0.547648429894388", 贡献百分比 = "0.1" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "标准强度", 权重 = "0.628130085182893", 贡献百分比 = "0.172" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "强度", 权重 = "-0.10947638732718", 贡献百分比 = "-0.03" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "保留时间差异", 权重 = "-0.768944834471997", 贡献百分比 = "0.067" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "库强度点积", 权重 = "1.91473647678043", 贡献百分比 = "0.071" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "形状（权重）", 权重 = "0.964673347739591", 贡献百分比 = "0.064" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "共洗脱（权重）", 权重 = "0.0265095737294209", 贡献百分比 = "-0.023" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "共洗脱计数", 权重 = "0.182160151225063", 贡献百分比 = "0.062" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "噪声信号", 权重 = "0.222902489204878", 贡献百分比 = "0.053" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考强度点积", 权重 = "0.552867011319634", 贡献百分比 = "0.023" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考形状（权重）", 权重 = "6.54328045047817", 贡献百分比 = "0.406" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考共洗脱（权重）", 权重 = "-0.035670415865123", 贡献百分比 = "0.028" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考共洗脱计数", 权重 = "0.528458461601712", 贡献百分比 = "0.099" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "标准强度", 权重 = "0.658504481008043", 贡献百分比 = "0.181" }
 重新合并 > 峰得分模型 > 采用诱饵 是 真
 重新合并 > 峰得分模型 > 采用次优峰值 是 假
 重新合并 > 积分所有峰 是 真
@@ -88,63 +88,63 @@ Extra Info: 峰得分模型 = "test1":
     [
         {
             得分名称 = "强度",
-            权重 = "-0.078328345434545",
-            贡献百分比 = "-0.021"
+            权重 = "-0.10947638732718",
+            贡献百分比 = "-0.03"
         },
         {
             得分名称 = "保留时间差异",
-            权重 = "-0.74923684676032",
-            贡献百分比 = "0.066"
+            权重 = "-0.768944834471997",
+            贡献百分比 = "0.067"
         },
         {
             得分名称 = "库强度点积",
-            权重 = "2.24238344148558",
-            贡献百分比 = "0.081"
+            权重 = "1.91473647678043",
+            贡献百分比 = "0.071"
         },
         {
             得分名称 = "形状（权重）",
-            权重 = "1.20618462186508",
-            贡献百分比 = "0.081"
+            权重 = "0.964673347739591",
+            贡献百分比 = "0.064"
         },
         {
             得分名称 = "共洗脱（权重）",
-            权重 = "0.0330641179011537",
-            贡献百分比 = "-0.031"
+            权重 = "0.0265095737294209",
+            贡献百分比 = "-0.023"
         },
         {
             得分名称 = "共洗脱计数",
-            权重 = "0.151546153152723",
-            贡献百分比 = "0.05"
+            权重 = "0.182160151225063",
+            贡献百分比 = "0.062"
         },
         {
             得分名称 = "噪声信号",
-            权重 = "0.176740916361492",
-            贡献百分比 = "0.042"
+            权重 = "0.222902489204878",
+            贡献百分比 = "0.053"
         },
         {
             得分名称 = "参考强度点积",
-            权重 = "0.498299821042048",
-            贡献百分比 = "0.02"
+            权重 = "0.552867011319634",
+            贡献百分比 = "0.023"
         },
         {
             得分名称 = "参考形状（权重）",
-            权重 = "6.39974546904101",
-            贡献百分比 = "0.4"
+            权重 = "6.54328045047817",
+            贡献百分比 = "0.406"
         },
         {
             得分名称 = "参考共洗脱（权重）",
-            权重 = "-0.0482245507469112",
-            贡献百分比 = "0.04"
+            权重 = "-0.035670415865123",
+            贡献百分比 = "0.028"
         },
         {
             得分名称 = "参考共洗脱计数",
-            权重 = "0.547648429894388",
-            贡献百分比 = "0.1"
+            权重 = "0.528458461601712",
+            贡献百分比 = "0.099"
         },
         {
             得分名称 = "标准强度",
-            权重 = "0.628130085182893",
-            贡献百分比 = "0.172"
+            权重 = "0.658504481008043",
+            贡献百分比 = "0.181"
         }
     ],
     采用诱饵 = 真,
@@ -158,18 +158,18 @@ Summary   : 已使用“test1”重新合并峰
 All Info  :
 已使用“test1”重新合并峰
 重新合并 > 峰得分模型 是 "test1"
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "强度", 权重 = "-0.078328345434545", 贡献百分比 = "-0.021" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "保留时间差异", 权重 = "-0.74923684676032", 贡献百分比 = "0.066" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "库强度点积", 权重 = "2.24238344148558", 贡献百分比 = "0.081" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "形状（权重）", 权重 = "1.20618462186508", 贡献百分比 = "0.081" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "共洗脱（权重）", 权重 = "0.0330641179011537", 贡献百分比 = "-0.031" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "共洗脱计数", 权重 = "0.151546153152723", 贡献百分比 = "0.05" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "噪声信号", 权重 = "0.176740916361492", 贡献百分比 = "0.042" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考强度点积", 权重 = "0.498299821042048", 贡献百分比 = "0.02" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考形状（权重）", 权重 = "6.39974546904101", 贡献百分比 = "0.4" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考共洗脱（权重）", 权重 = "-0.0482245507469112", 贡献百分比 = "0.04" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考共洗脱计数", 权重 = "0.547648429894388", 贡献百分比 = "0.1" }
-重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "标准强度", 权重 = "0.628130085182893", 贡献百分比 = "0.172" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "强度", 权重 = "-0.10947638732718", 贡献百分比 = "-0.03" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "保留时间差异", 权重 = "-0.768944834471997", 贡献百分比 = "0.067" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "库强度点积", 权重 = "1.91473647678043", 贡献百分比 = "0.071" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "形状（权重）", 权重 = "0.964673347739591", 贡献百分比 = "0.064" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "共洗脱（权重）", 权重 = "0.0265095737294209", 贡献百分比 = "-0.023" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "共洗脱计数", 权重 = "0.182160151225063", 贡献百分比 = "0.062" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "噪声信号", 权重 = "0.222902489204878", 贡献百分比 = "0.053" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考强度点积", 权重 = "0.552867011319634", 贡献百分比 = "0.023" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考形状（权重）", 权重 = "6.54328045047817", 贡献百分比 = "0.406" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考共洗脱（权重）", 权重 = "-0.035670415865123", 贡献百分比 = "0.028" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "参考共洗脱计数", 权重 = "0.528458461601712", 贡献百分比 = "0.099" }
+重新合并 > 峰得分模型 > 特征得分 : 包含 { 得分名称 = "标准强度", 权重 = "0.658504481008043", 贡献百分比 = "0.181" }
 重新合并 > 峰得分模型 > 采用诱饵 是 真
 重新合并 > 峰得分模型 > 采用次优峰值 是 假
 重新合并 > 仅积分有显著性 q 值的峰 是 真
@@ -181,63 +181,63 @@ Extra Info: 峰得分模型 = "test1":
     [
         {
             得分名称 = "强度",
-            权重 = "-0.078328345434545",
-            贡献百分比 = "-0.021"
+            权重 = "-0.10947638732718",
+            贡献百分比 = "-0.03"
         },
         {
             得分名称 = "保留时间差异",
-            权重 = "-0.74923684676032",
-            贡献百分比 = "0.066"
+            权重 = "-0.768944834471997",
+            贡献百分比 = "0.067"
         },
         {
             得分名称 = "库强度点积",
-            权重 = "2.24238344148558",
-            贡献百分比 = "0.081"
+            权重 = "1.91473647678043",
+            贡献百分比 = "0.071"
         },
         {
             得分名称 = "形状（权重）",
-            权重 = "1.20618462186508",
-            贡献百分比 = "0.081"
+            权重 = "0.964673347739591",
+            贡献百分比 = "0.064"
         },
         {
             得分名称 = "共洗脱（权重）",
-            权重 = "0.0330641179011537",
-            贡献百分比 = "-0.031"
+            权重 = "0.0265095737294209",
+            贡献百分比 = "-0.023"
         },
         {
             得分名称 = "共洗脱计数",
-            权重 = "0.151546153152723",
-            贡献百分比 = "0.05"
+            权重 = "0.182160151225063",
+            贡献百分比 = "0.062"
         },
         {
             得分名称 = "噪声信号",
-            权重 = "0.176740916361492",
-            贡献百分比 = "0.042"
+            权重 = "0.222902489204878",
+            贡献百分比 = "0.053"
         },
         {
             得分名称 = "参考强度点积",
-            权重 = "0.498299821042048",
-            贡献百分比 = "0.02"
+            权重 = "0.552867011319634",
+            贡献百分比 = "0.023"
         },
         {
             得分名称 = "参考形状（权重）",
-            权重 = "6.39974546904101",
-            贡献百分比 = "0.4"
+            权重 = "6.54328045047817",
+            贡献百分比 = "0.406"
         },
         {
             得分名称 = "参考共洗脱（权重）",
-            权重 = "-0.0482245507469112",
-            贡献百分比 = "0.04"
+            权重 = "-0.035670415865123",
+            贡献百分比 = "0.028"
         },
         {
             得分名称 = "参考共洗脱计数",
-            权重 = "0.547648429894388",
-            贡献百分比 = "0.1"
+            权重 = "0.528458461601712",
+            贡献百分比 = "0.099"
         },
         {
             得分名称 = "标准强度",
-            权重 = "0.628130085182893",
-            贡献百分比 = "0.172"
+            权重 = "0.658504481008043",
+            贡献百分比 = "0.181"
         }
     ],
     采用诱饵 = 真,
diff --git a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/zh/TestSrmTutorialLegacy.log b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/zh/TestSrmTutorialLegacy.log
index c286f1a614..d23b2c90c5 100644
--- a/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/zh/TestSrmTutorialLegacy.log
+++ b/pwiz_tools/Skyline/TestTutorial/TutorialAuditLogs/zh/TestSrmTutorialLegacy.log
@@ -307,8 +307,8 @@ Summary   : 设置 > 离子对设置 已更改
 All Info  :
 离子对设置 已更改
 设置 > 离子对设置 -- 预测 > 碰撞能量 从 "SCIEX" 更改到 "SRMcourse_20140211_Parameters_custom-CE-equation"
-设置 > 离子对设置 -- 预测 > 碰撞能量 > 回归参数 : 包含 { 电荷 = "2", 斜率 = "0.0369", 截距 = "3.9361" }
-设置 > 离子对设置 -- 预测 > 碰撞能量 > 回归参数 : 包含 { 电荷 = "3", 斜率 = "0.0208", 截距 = "9.0837" }
+设置 > 离子对设置 -- 预测 > 碰撞能量 > 回归参数 : 包含 { 电荷 = "2", 斜率 = "0.025", 截距 = "8.6852" }
+设置 > 离子对设置 -- 预测 > 碰撞能量 > 回归参数 : 包含 { 电荷 = "3", 斜率 = "0.046", 截距 = "-1.9754" }
 设置 > 离子对设置 -- 仪器 > 方法匹配耐受性质荷比 从 "0.055" 更改到 "0.01"
 
 Undo Redo : 已管理结果
diff --git a/pwiz_tools/commandline/msconvert.cpp b/pwiz_tools/commandline/msconvert.cpp
index 00b8cc75a3..eb4bda1112 100644
--- a/pwiz_tools/commandline/msconvert.cpp
+++ b/pwiz_tools/commandline/msconvert.cpp
@@ -71,15 +71,8 @@ struct Config : public Reader::Config
     Config()
         : outputPath("."), verbose(false), merge(false)
     {
-        simAsSpectra = false;
-        srmAsSpectra = false;
-        combineIonMobilitySpectra = false;
-        ignoreCalibrationScans = false;
-        reportSonarBins = false;
-        unknownInstrumentIsError = true;
         stripLocationFromSourceFiles = false;
         stripVersionFromSoftware = false;
-        ddaProcessing = false;
     }
 
     string outputFilename(const string& inputFilename, const MSData& inputMSData) const;