{"id":"W2138093970","doi":"10.1074/mcp.m800555-mcp200","title":"Finding Chimeras: a Bioinformatics Strategy for Identification of Cross-linked Peptides","year":2009,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Research Resources; U.S. Public Health Service; National Institutes of Health","keywords":"Context (archaeology); Computational biology; Identification (biology); Computer science; Network topology; Chemistry; Bioinformatics; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003793877,0.0002423804,0.0002364917,0.00008362494,0.0001093565,0.00008104382,0.0003111051,0.0002830323,0.000002002743],"category_scores_gemma":[0.000161206,0.0002513999,0.000225451,0.0001285645,0.00009324995,0.00002028311,0.000054526,0.0001130004,0.000002770209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002988398,"about_ca_system_score_gemma":0.0001155988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003615163,"about_ca_topic_score_gemma":8.235107e-7,"domain_scores_codex":[0.998512,0.00003565579,0.0006167071,0.0002913985,0.0001818018,0.0003624151],"domain_scores_gemma":[0.998789,0.000006936266,0.0003850794,0.0005271471,0.0002040868,0.00008771769],"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":[0.00008877848,0.00004193817,0.0001620321,0.00008072354,0.00004895662,0.000001238816,0.00006116684,0.003588374,0.9921512,0.001778332,0.00002730754,0.001969935],"study_design_scores_gemma":[0.0006249709,0.0003615301,0.0005596975,0.00001728019,0.00003559152,0.000009381041,0.00003334546,0.0087556,0.9862427,0.002826185,0.0002573009,0.0002763843],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6502004,0.0003650845,0.3482648,0.00002068548,0.00006422021,0.0008428512,0.000046037,0.00001447936,0.000181437],"genre_scores_gemma":[0.9596908,0.00003652531,0.03923675,0.0001361234,0.0001102785,0.00006137766,0.0005456284,0.00003163449,0.0001508723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3094904,"threshold_uncertainty_score":0.9999938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01176442050378905,"score_gpt":0.277743804116598,"score_spread":0.2659793836128089,"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."}}