{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01670216,0.003389888,0.002471089,0.004111696,0.001107054,0.0036463,0.003384787,0.001992746,0.003721592],"category_scores_gemma":[0.02778248,0.0009181433,0.001873263,0.001676973,0.0009143801,0.002306734,0.005031664,0.001963875,0.003302888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001204397,"about_ca_system_score_gemma":0.001945657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002845783,"about_ca_topic_score_gemma":0.002454408,"domain_scores_codex":[0.9884144,0.004127536,0.0007461946,0.002041301,0.003946539,0.000723977],"domain_scores_gemma":[0.9819228,0.007578298,0.001900471,0.004251709,0.00350763,0.0008390691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008560751,0.00208659,0.1159407,0.002836723,0.002107026,0.001565545,0.005436144,0.4170051,0.08299753,0.008904344,0.03924368,0.3133159],"study_design_scores_gemma":[0.0001593699,0.0008984896,0.01702001,0.0001301846,0.0001435252,0.0005163722,0.0005657768,0.9300273,0.03944911,0.003595588,0.007329521,0.0001647361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6644838,0.001693238,0.279305,0.0003466409,0.0002456381,0.0009140333,0.003145208,0.03938232,0.01048408],"genre_scores_gemma":[0.800448,0.0004359231,0.1832867,0.0001810669,0.00005007393,0.0008378144,0.01069269,0.001776348,0.002291363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01670216,"threshold_uncertainty_score":0.08833051,"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."}}