{"id":"W1966666048","doi":"10.1002/pmic.201200338","title":"Unifying protein inference and peptide identification with feedback to update consistency between peptides","year":2012,"lang":"en","type":"article","venue":"PROTEOMICS","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Inference; Peptide; Identification (biology); Computer science; Consistency (knowledge bases); Computational biology; Artificial intelligence; Biology; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002048443,0.000203901,0.0001958266,0.00005426189,0.0002247587,0.00008794052,0.00020912,0.0001018713,0.00003047035],"category_scores_gemma":[0.00008000308,0.0001922374,0.00002632548,0.0001682736,0.0001037047,0.0003217389,0.0001369822,0.0002405821,0.00005024395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007405713,"about_ca_system_score_gemma":0.0000422661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000288443,"about_ca_topic_score_gemma":0.000006421998,"domain_scores_codex":[0.9988469,0.00001235185,0.0003154137,0.0003257261,0.0001420981,0.0003574786],"domain_scores_gemma":[0.9989938,0.00003645994,0.0001981092,0.0004506794,0.0001081205,0.0002129011],"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":[0.00004566383,0.00006284726,0.09360345,0.0002281852,0.00003178809,5.782526e-7,0.0003361309,0.00001687491,0.877203,0.02142889,0.00002779002,0.007014726],"study_design_scores_gemma":[0.0002368727,0.00002806563,0.004717556,0.0001674877,0.00003092681,0.000008765218,0.0001512145,0.0000448183,0.9830188,0.008603983,0.00257361,0.0004179727],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8140495,0.00004857139,0.1833152,0.000381484,0.000005152885,0.0008965547,0.00004315033,0.0001717421,0.001088585],"genre_scores_gemma":[0.6998842,0.00001910937,0.2987674,0.00003401627,0.00008409339,0.0008589627,0.00003248268,0.00002954232,0.0002901907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1154522,"threshold_uncertainty_score":0.7839215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02274177817366885,"score_gpt":0.2844379980075201,"score_spread":0.2616962198338512,"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."}}