{"id":"W2154813243","doi":"10.1002/prot.22850","title":"Blind predictions of protein interfaces by docking calculations in CAPRI","year":2010,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Docking (animal); Computer science; Extant taxon; Protein function; Macromolecular docking; Protein–protein interaction; Computational biology; Data mining; Biological system; Protein structure; Chemistry; Biology; Medicine; 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":[0.00009864392,0.0001669788,0.000148976,0.0001127075,0.00009788193,0.00003490485,0.0001038482,0.0002724419,0.00003190337],"category_scores_gemma":[0.0000809487,0.0001404098,0.00003759401,0.0001701113,0.0001262303,0.00002570898,0.00007828065,0.0002849601,6.884306e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008121064,"about_ca_system_score_gemma":0.00005369349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004537752,"about_ca_topic_score_gemma":0.0004923113,"domain_scores_codex":[0.9991171,0.00001789177,0.0003832118,0.0001671704,0.0001391615,0.0001754589],"domain_scores_gemma":[0.9994217,0.000004916275,0.000179472,0.0002406523,0.00008702498,0.00006628999],"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":[0.0001402035,0.00002968322,0.003333815,0.00012192,0.00003649101,1.565498e-7,0.0001746857,0.0002000557,0.98567,0.0009295627,0.0001066419,0.009256782],"study_design_scores_gemma":[0.005666009,0.001524419,0.02175509,0.0001728515,0.0001116841,0.0001139811,0.0009068862,0.0402294,0.8946985,0.006808488,0.02681635,0.001196348],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9652609,0.0001354793,0.03289248,0.00008037895,0.0002006395,0.0007690999,0.0001471338,0.00001873512,0.0004951849],"genre_scores_gemma":[0.9867182,0.00001472921,0.0127805,0.00005377133,0.00007860957,0.00003451207,0.0002202115,0.00001156362,0.00008788234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0909715,"threshold_uncertainty_score":0.5725746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004155056860339734,"score_gpt":0.2153989422427763,"score_spread":0.2112438853824366,"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."}}