{"id":"W1920328788","doi":"10.1002/0471250953.bi1314s31","title":"Predicting Peptide Retention Times for Proteomics","year":2010,"lang":"en","type":"article","venue":"Current Protocols in Bioinformatics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Retention time; Chromatography; Proteomics; Fractionation; Chemistry; Peptide; Mass spectrometry; Computer science; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002949857,0.0001797164,0.0001759457,0.00007080071,0.000136912,0.00007606968,0.00033529,0.0001603359,0.00006647888],"category_scores_gemma":[0.0001916928,0.0001744548,0.00008655463,0.000126514,0.00006747013,0.0003318166,0.00009539405,0.0005555906,0.00001160864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005675684,"about_ca_system_score_gemma":0.0000662638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001408352,"about_ca_topic_score_gemma":0.000005566888,"domain_scores_codex":[0.9987047,0.00000342747,0.0006620575,0.000179473,0.0001444741,0.000305908],"domain_scores_gemma":[0.9989702,0.00004943724,0.0003578736,0.0004485588,0.0001046555,0.00006923817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004276712,0.001430004,0.07173062,0.01588217,0.00004929886,9.699841e-7,0.002042577,0.0002844426,0.3938982,0.1286455,0.004586057,0.3810225],"study_design_scores_gemma":[0.002333655,0.0001020862,0.0001381744,0.001262418,0.00002013493,0.00001396329,0.000182446,0.2190833,0.5262516,0.05062166,0.1991873,0.0008032178],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1195122,0.0000180166,0.6255193,0.0002274673,0.0002720077,0.2303717,0.0004549589,0.00115393,0.02247051],"genre_scores_gemma":[0.005825812,0.00000774726,0.6252787,0.00001460029,0.0001833889,0.3683327,0.0001435664,0.00003089525,0.0001825628],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3802193,"threshold_uncertainty_score":0.711406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03341266430213969,"score_gpt":0.3475060992545571,"score_spread":0.3140934349524174,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}