diff --git a/cerulean_cloud/cloud_function_ais_analysis/main.py b/cerulean_cloud/cloud_function_ais_analysis/main.py
index cd827862..7fb8e1e7 100644
--- a/cerulean_cloud/cloud_function_ais_analysis/main.py
+++ b/cerulean_cloud/cloud_function_ais_analysis/main.py
@@ -3,6 +3,7 @@
 
 import asyncio
 import os
+from json import loads
 
 import geopandas as gpd
 from shapely import wkb
@@ -107,7 +108,7 @@ async def handle_aaa_request(request):
                                         slick=slick.id,
                                         coincidence_score=traj["total_score"],
                                         rank=idx + 1,
-                                        geojson_fc=single_track.to_json(),
+                                        geojson_fc=loads(single_track.to_json()),
                                         geometry=LineString(
                                             single_track["geometry"]
                                         ).wkt,
diff --git a/cerulean_cloud/cloud_function_ais_analysis/utils/constants.py b/cerulean_cloud/cloud_function_ais_analysis/utils/constants.py
index 8ac4627e..dbbaf2c7 100644
--- a/cerulean_cloud/cloud_function_ais_analysis/utils/constants.py
+++ b/cerulean_cloud/cloud_function_ais_analysis/utils/constants.py
@@ -10,8 +10,8 @@
 
 # buffering parameters for AIS trajectories
 AIS_BUFFER = 5000  # buffer around GRD envelope to capture AIS
-SPREAD_RATE = 2000  # meters/hour perpendicular to vessel track
-BUF_START = 500
+SPREAD_RATE = 1000  # meters/hour perpendicular to vessel track
+BUF_START = 100
 BUF_END = BUF_START + SPREAD_RATE * TOTAL_TIME
 BUF_VEC = np.linspace(BUF_START, BUF_END, NUM_TIMESTEPS)
 
diff --git a/cerulean_cloud/cloud_function_ais_analysis/utils/scoring.py b/cerulean_cloud/cloud_function_ais_analysis/utils/scoring.py
index ed21fda0..455a061c 100644
--- a/cerulean_cloud/cloud_function_ais_analysis/utils/scoring.py
+++ b/cerulean_cloud/cloud_function_ais_analysis/utils/scoring.py
@@ -97,6 +97,7 @@ def compute_overlap_score(
         float: overlap score between buffered_traj and slick
     """
     overlap_score = slick.intersection(buffered_traj).area / slick.area
+    # XXX this strongly benefits smaller slicks
     return overlap_score
 
 
diff --git a/cerulean_cloud/database_client.py b/cerulean_cloud/database_client.py
index cccd9e11..b8b2bf07 100644
--- a/cerulean_cloud/database_client.py
+++ b/cerulean_cloud/database_client.py
@@ -195,12 +195,15 @@ async def insert_slick_to_source(self, **kwargs):
         """add a new slick_to_source"""
         return await insert(self.session, db.SlickToSource, **kwargs)
 
-    async def get_slicks_without_sources_from_scene_id(self, scene_id, active=True):
+    async def get_slicks_without_sources_from_scene_id(
+        self, scene_id, min_conf=0.5, active=True
+    ):
         """
         Asynchronously queries the database to fetch slicks without associated sources for a given scene ID.
 
         Args:
             scene_id (str): The ID of the scene for which slicks are needed.
+            min_conf (float): Minimum machine confidence for slicks to return. Default is 0.5.
             active (bool): Flag to filter slicks based on their active status. Default is True.
 
         Returns:
@@ -222,6 +225,7 @@ async def get_slicks_without_sources_from_scene_id(self, scene_id, active=True):
                     db.SlickToSource.slick == None,  # noqa
                     db.Sentinel1Grd.scene_id == scene_id,
                     db.Slick.active == active,
+                    db.Slick.machine_confidence > min_conf,
                 )
             )
         )