{"id":"W2018410079","doi":"10.1002/prot.21804","title":"Docking and scoring protein complexes: CAPRI 3rd Edition","year":2007,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"Enzyme Structure and Function","field":"Materials Science","cited_by":355,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Institute of Genetics; Canadian Institutes of Health Research; University of Toronto","keywords":"Docking (animal); Computational biology; Computer science; Artificial intelligence; Machine learning; Biology; Medicine","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":[0.0003882012,0.0002280952,0.0001965091,0.0001629907,0.0004515015,0.0002112999,0.0000712751,0.0001649294,0.0002018667],"category_scores_gemma":[0.00005891081,0.0001784975,0.00002917962,0.0001851331,0.0001317712,0.0006970005,0.00007395389,0.0002224435,0.00001232636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004207683,"about_ca_system_score_gemma":0.00002320622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003890445,"about_ca_topic_score_gemma":0.0000894121,"domain_scores_codex":[0.9986781,0.00002101805,0.0004327833,0.0002236953,0.000307843,0.0003365506],"domain_scores_gemma":[0.999333,0.00002551591,0.0002262168,0.0001794801,0.00009947619,0.0001363564],"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":[0.0002139975,0.00001232401,0.0009515644,0.0005265212,0.00001679269,0.000002136498,0.001013761,0.00002545908,0.9461839,0.007339426,0.0002251696,0.04348894],"study_design_scores_gemma":[0.003151515,0.001252638,0.04906393,0.0004746837,0.0001491113,0.0004161223,0.003569819,0.004248369,0.8907916,0.02724855,0.01820443,0.001429245],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8633336,0.0001337859,0.1331191,0.00008320615,0.0009105887,0.0007635686,0.00003016902,0.0001931715,0.00143281],"genre_scores_gemma":[0.9715131,0.000008946261,0.02756319,0.0002477979,0.0005521911,0.00001161154,0.00003106109,0.00001457404,0.00005752461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1081795,"threshold_uncertainty_score":0.7278919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009686016743464136,"score_gpt":0.2151971343064413,"score_spread":0.2055111175629772,"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."}}