{"id":"W2165531467","doi":"10.1002/prot.24428","title":"Docking, scoring, and affinity prediction in CAPRI","year":2013,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":249,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Canada Research Chairs; Hospital for Sick Children; University of Toronto","funders":"Agence Nationale de la Recherche","keywords":"Docking (animal); Computer science; Artificial intelligence; Computational biology; Biology; Medicine","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":[0.00007775809,0.0001717995,0.0001262949,0.00008521804,0.0001043297,0.00008388788,0.00005938139,0.0002145623,0.0000464305],"category_scores_gemma":[0.00005004208,0.0001403948,0.00002312877,0.00009463714,0.00007617422,0.00003676327,0.00009816078,0.0001657886,0.000003568822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001268046,"about_ca_system_score_gemma":0.00002725899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007165717,"about_ca_topic_score_gemma":0.0001161711,"domain_scores_codex":[0.9992256,0.00001918306,0.0002605482,0.0001856437,0.0001111175,0.0001978738],"domain_scores_gemma":[0.9995717,0.000003917557,0.00009913003,0.0001817252,0.00005694363,0.00008656164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004396094,0.00009670276,0.289775,0.001229725,0.000199477,0.000002678461,0.001223561,0.0005114638,0.373603,0.004003366,0.002493701,0.3264216],"study_design_scores_gemma":[0.005573675,0.002334218,0.8464423,0.0001910348,0.00009808261,0.000333797,0.001298749,0.04263592,0.0544842,0.02277152,0.02228013,0.001556352],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894867,0.0002656765,0.008263084,0.00007395539,0.0001913472,0.0007017297,0.00002962206,0.00002809522,0.0009597952],"genre_scores_gemma":[0.9910147,0.00009509333,0.008252472,0.0002517402,0.0001333585,0.00003632101,0.00009931694,0.00001072847,0.0001062788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5566673,"threshold_uncertainty_score":0.5725133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004166134472791118,"score_gpt":0.1880848308742308,"score_spread":0.1839186964014396,"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."}}