From 1f8e4b3aa317f9ac013224862d29f3c855b07d1b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jochen=20Nie=C3=9Fer?= Date: Sun, 1 Dec 2024 21:16:24 +0100 Subject: [PATCH] spell out all journal names in bibliography --- docs/source/literature.bib | 74 +++++++++++++++++--------------------- paper/literature.bib | 18 +++++----- 2 files changed, 41 insertions(+), 51 deletions(-) diff --git a/docs/source/literature.bib b/docs/source/literature.bib index bc524d3..7b122c6 100644 --- a/docs/source/literature.bib +++ b/docs/source/literature.bib @@ -46,7 +46,7 @@ @article{matplotlib @misc{matplotlibzenodo, author = {{The Matplotlib Development Team}}, - title = {Matplotlib: Visualization with Python}, + title = {{Matplotlib: Visualization with Python}}, keywords = {software}, month = may, year = 2024, @@ -58,17 +58,16 @@ @misc{matplotlibzenodo @article{RN173, author = {Hoffmann, Matthew D. and Gelman, Andrew}, - title = {The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo}, + title = {{The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo}}, journal = {Journal of Machine Learning Research}, volume = {15}, year = {2014}, - type = {Journal Article} } @article{RN150, author = {Abril-Pla, O. and Andreani, V. and Carroll, C. and Dong, L. and Fonnesbeck, C. J. and Kochurov, M. and Kumar, R. and Lao, J. and Luhmann, C. C. and Martin, O. A. and Osthege, M. and Vieira, R. and Wiecki, T. and Zinkov, R.}, - title = {{PyMC}: a modern, and comprehensive probabilistic programming framework in Python}, - journal = {PeerJ Comput Sci}, + title = {{PyMC}: a modern, and comprehensive probabilistic programming framework in {P}ython}, + journal = {PeerJ Computer Science}, volume = {9}, pages = {e1516}, issn = {2376-5992 (Electronic) @@ -76,47 +75,44 @@ @article{RN150 doi = {10.7717/peerj-cs.1516}, url = {https://www.ncbi.nlm.nih.gov/pubmed/37705656}, year = {2023}, - type = {Journal Article} } @book{RN162, author = {Kruschke, John K.}, - title = {Doing Bayesian Data Analysis}, + title = {{Doing Bayesian Data Analysis}}, edition = {Second Edition}, publisher={Academic Press}, isbn = {9780123814852}, year = {2015}, type = {Book}, - doi = {http://dx.doi.org/10.1016/B978-0-12-405888-0.00001-5} + doi = {10.1016/B978-0-12-405888-0.00001-5} } @article{RN144, author = {Azzalini, A.}, title = {A class of distributions which includes the normal ones}, - journal = {Scand. J. Statist.}, + journal = {Scandinavian Journal of Statistics}, volume = {12}, pages = {171-178}, year = {1985}, - type = {Journal Article}, url = {http://www.jstor.org/stable/4615982}, } @article{RN152, author = {Gelman, Andrew and Rubin, Donald B.}, - title = {Inference from Iterative Simulation Using Multiple Sequences}, + title = {{Inference from Iterative Simulation Using Multiple Sequences}}, journal = {Statistical Science}, volume = {7}, number = {4}, year = {1992}, - type = {Journal Article}, doi = {10.1214/ss/1177011136} } @article{RN153, author = {Grushka, E.}, - title = {Characterization of exponentially modified Gaussian peaks in chromatography}, - journal = {Anal Chem}, + title = {{Characterization of exponentially modified Gaussian peaks in chromatography}}, + journal = {Analytical Chemistry}, volume = {44}, number = {11}, pages = {1733-8}, @@ -125,13 +121,12 @@ @article{RN153 doi = {10.1021/ac60319a011}, url = {https://www.ncbi.nlm.nih.gov/pubmed/22324584}, year = {1972}, - type = {Journal Article} } @article{RN149, author = {Hemmerich, J. and Noack, S. and Wiechert, W. and Oldiges, M.}, - title = {Microbioreactor Systems for Accelerated Bioprocess Development}, - journal = {Biotechnol J}, + title = {{Microbioreactor Systems for Accelerated Bioprocess Development}}, + journal = {Biotechnology Journal}, volume = {13}, number = {4}, pages = {e1700141}, @@ -140,13 +135,12 @@ @article{RN149 doi = {10.1002/biot.201700141}, url = {https://www.ncbi.nlm.nih.gov/pubmed/29283217}, year = {2018}, - type = {Journal Article} } @article{RN148, author = {Kostov, Y. and Harms, P. and Randers-Eichhorn, L. and Rao, G.}, title = {Low-cost microbioreactor for high-throughput bioprocessing}, - journal = {Biotechnol Bioeng}, + journal = {Biotechnology and Bioengineering}, volume = {72}, number = {3}, pages = {346-52}, @@ -155,12 +149,11 @@ @article{RN148 doi = {10.1002/1097-0290(20010205)72:3<346::aid-bit12>3.0.co;2-x}, url = {https://www.ncbi.nlm.nih.gov/pubmed/11135205}, year = {2001}, - type = {Journal Article} } @article{RN145, author = {Vehtari, Aki and Gelman, Andrew and Gabry, Jonah}, - title = {Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC}, + title = {{Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC}}, journal = {Statistics and Computing}, volume = {27}, number = {5}, @@ -169,29 +162,26 @@ @article{RN145 1573-1375}, doi = {10.1007/s11222-016-9696-4}, year = {2016}, - type = {Journal Article} } @article{RN146, author = {Watanabe, Sumio}, - title = {Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory}, - journal = {Journal of machine learning research}, + title = {{Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory}}, + journal = {Journal of Machine Learning Research}, volume = {11}, pages = {3571-3594}, year = {2010}, - type = {Journal Article}, } @article{RN147, author = {Kumar, Ravin and Carroll, Colin and Hartikainen, Ari and Martin, Osvaldo}, - title = {ArviZ a unified library for exploratory analysis of Bayesian models in Python}, + title = {{ArviZ a unified library for exploratory analysis of Bayesian models in Python}}, journal = {Journal of Open Source Software}, volume = {4}, number = {33}, issn = {2475-9066}, doi = {10.21105/joss.01143}, year = {2019}, - type = {Journal Article} } @article{harris2020array, @@ -217,60 +207,60 @@ @article{harris2020array } @article{vivo2012bayesian, - title={Bayesian approach for peak detection in two-dimensional chromatography}, + title={{Bayesian approach for peak detection in two-dimensional chromatography}}, author={Viv{\'o}-Truyols, Gabriel}, - journal={Analytical chemistry}, + journal={Analytical Chemistry}, volume={84}, number={6}, pages={2622--2630}, year={2012}, - doi={https://doi.org/10.1021/ac202124t}, + doi={10.1021/ac202124t}, publisher={ACS Publications} } @article{woldegebriel2015probabilistic, - title={Probabilistic model for untargeted peak detection in LC--MS using Bayesian statistics}, + title={{Probabilistic model for untargeted peak detection in LC--MS using Bayesian statistics}}, author={Woldegebriel, Michael and Viv{\'o}-Truyols, Gabriel}, - journal={Analytical chemistry}, + journal={Analytical Chemistry}, volume={87}, number={14}, pages={7345--7355}, year={2015}, - doi={https://doi.org/10.1021/acs.analchem.5b01521}, + doi={10.1021/acs.analchem.5b01521}, publisher={ACS Publications} } @article{briskot2019prediction, - title={Prediction uncertainty assessment of chromatography models using Bayesian inference}, + title={{Prediction uncertainty assessment of chromatography models using Bayesian inference}}, author={Briskot, Till and St\"{u}ckler, Ferdinand and Wittkopp, Felix and Williams, Christopher and Yang, Jessica and Konrad, Susanne and Doninger, Katharina and Griesbach, Jan and Bennecke, Moritz and Hepbildikler, Stefan and others}, journal={Journal of Chromatography A}, volume={1587}, pages={101--110}, year={2019}, - doi={https://doi.org/10.1016/j.chroma.2018.11.076}, + doi={10.1016/j.chroma.2018.11.076}, publisher={Elsevier} } @article{yamamoto2021uncertainty, - title={Uncertainty quantification for chromatography model parameters by Bayesian inference using sequential Monte Carlo method}, + title={{Uncertainty quantification for chromatography model parameters by Bayesian inference using sequential Monte Carlo method}}, author={Yamamoto, Yota and Yajima, Tomoyuki and Kawajiri, Yoshiaki}, journal={Chemical Engineering Research and Design}, volume={175}, pages={223--237}, year={2021}, - doi={https://doi.org/10.1016/j.cherd.2021.09.003}, + doi={10.1016/j.cherd.2021.09.003}, publisher={Elsevier} } @article{wiczling2016much, - title={How much can we learn from a single chromatographic experiment? A Bayesian perspective}, + title={{How much can we learn from a single chromatographic experiment? A Bayesian perspective}}, author={Wiczling, Pawe{\l} and Kaliszan, Roman}, - journal={Analytical chemistry}, + journal={Analytical Chemistry}, volume={88}, number={1}, pages={997--1002}, year={2016}, - doi={https://doi.org/10.1021/acs.analchem.5b03859}, + doi={10.1021/acs.analchem.5b03859}, publisher={ACS Publications} } @@ -282,7 +272,7 @@ @article{kelly1971estimation number={10}, pages={1170--1183}, year={1971}, - doi={https://doi.org/10.1021/ac60304a011}, + doi={10.1021/ac60304a011}, publisher={ACS Publications} } @@ -294,6 +284,6 @@ @article{kelly1971application number={10}, pages={1184--1195}, year={1971}, - doi={https://doi.org/10.1021/ac60304a005}, + doi={10.1021/ac60304a005}, publisher={ACS Publications} } diff --git a/paper/literature.bib b/paper/literature.bib index 051ede5..7b122c6 100644 --- a/paper/literature.bib +++ b/paper/literature.bib @@ -67,7 +67,7 @@ @article{RN173 @article{RN150, author = {Abril-Pla, O. and Andreani, V. and Carroll, C. and Dong, L. and Fonnesbeck, C. J. and Kochurov, M. and Kumar, R. and Lao, J. and Luhmann, C. C. and Martin, O. A. and Osthege, M. and Vieira, R. and Wiecki, T. and Zinkov, R.}, title = {{PyMC}: a modern, and comprehensive probabilistic programming framework in {P}ython}, - journal = {PeerJ Comput Sci}, + journal = {PeerJ Computer Science}, volume = {9}, pages = {e1516}, issn = {2376-5992 (Electronic) @@ -91,7 +91,7 @@ @book{RN162 @article{RN144, author = {Azzalini, A.}, title = {A class of distributions which includes the normal ones}, - journal = {Scand. J. Statist.}, + journal = {Scandinavian Journal of Statistics}, volume = {12}, pages = {171-178}, year = {1985}, @@ -112,7 +112,7 @@ @article{RN152 @article{RN153, author = {Grushka, E.}, title = {{Characterization of exponentially modified Gaussian peaks in chromatography}}, - journal = {Anal Chem}, + journal = {Analytical Chemistry}, volume = {44}, number = {11}, pages = {1733-8}, @@ -126,7 +126,7 @@ @article{RN153 @article{RN149, author = {Hemmerich, J. and Noack, S. and Wiechert, W. and Oldiges, M.}, title = {{Microbioreactor Systems for Accelerated Bioprocess Development}}, - journal = {Biotechnol J}, + journal = {Biotechnology Journal}, volume = {13}, number = {4}, pages = {e1700141}, @@ -140,7 +140,7 @@ @article{RN149 @article{RN148, author = {Kostov, Y. and Harms, P. and Randers-Eichhorn, L. and Rao, G.}, title = {Low-cost microbioreactor for high-throughput bioprocessing}, - journal = {Biotechnol Bioeng}, + journal = {Biotechnology and Bioengineering}, volume = {72}, number = {3}, pages = {346-52}, @@ -167,7 +167,7 @@ @article{RN145 @article{RN146, author = {Watanabe, Sumio}, title = {{Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory}}, - journal = {Journal of machine learning research}, + journal = {Journal of Machine Learning Research}, volume = {11}, pages = {3571-3594}, year = {2010}, @@ -209,7 +209,7 @@ @article{harris2020array @article{vivo2012bayesian, title={{Bayesian approach for peak detection in two-dimensional chromatography}}, author={Viv{\'o}-Truyols, Gabriel}, - journal={Analytical chemistry}, + journal={Analytical Chemistry}, volume={84}, number={6}, pages={2622--2630}, @@ -221,7 +221,7 @@ @article{vivo2012bayesian @article{woldegebriel2015probabilistic, title={{Probabilistic model for untargeted peak detection in LC--MS using Bayesian statistics}}, author={Woldegebriel, Michael and Viv{\'o}-Truyols, Gabriel}, - journal={Analytical chemistry}, + journal={Analytical Chemistry}, volume={87}, number={14}, pages={7345--7355}, @@ -255,7 +255,7 @@ @article{yamamoto2021uncertainty @article{wiczling2016much, title={{How much can we learn from a single chromatographic experiment? A Bayesian perspective}}, author={Wiczling, Pawe{\l} and Kaliszan, Roman}, - journal={Analytical chemistry}, + journal={Analytical Chemistry}, volume={88}, number={1}, pages={997--1002},