{"id":"W2027403155","doi":"10.1002/prot.22818","title":"Docking and scoring protein interactions: CAPRI 2009","year":2010,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":235,"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; Protein–protein interaction; Web server; Computational biology; Artificial intelligence; Machine learning; Biology; Medicine; Biochemistry; The Internet; World Wide Web","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":[0.02169785,0.003412409,0.002171803,0.002965275,0.001504304,0.002270985,0.005098512,0.002567787,0.004265643],"category_scores_gemma":[0.01610309,0.0009727858,0.001684713,0.001970145,0.001246332,0.00172869,0.004330488,0.002690933,0.004376207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002893769,"about_ca_system_score_gemma":0.00271653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01028507,"about_ca_topic_score_gemma":0.009491226,"domain_scores_codex":[0.9816895,0.007462997,0.0009198305,0.002645611,0.005704694,0.001577374],"domain_scores_gemma":[0.9878279,0.003707602,0.0009243978,0.003031724,0.003602491,0.0009058638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01355498,0.005050711,0.06872749,0.001571092,0.001906404,0.0007928594,0.001220807,0.3008176,0.03898364,0.007850354,0.2140466,0.3454774],"study_design_scores_gemma":[0.0006638477,0.00269865,0.02325968,0.00007839049,0.0001249914,0.0004971698,0.0002454552,0.9176629,0.03240962,0.001890208,0.02024935,0.0002197568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7471381,0.002468938,0.1307471,0.001196389,0.0006524666,0.002641036,0.01951066,0.06626771,0.02937755],"genre_scores_gemma":[0.6833328,0.0005621523,0.2297483,0.0005727922,0.00009579185,0.001542529,0.07306183,0.002862344,0.008221408],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02169785,"threshold_uncertainty_score":0.1147506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006309381073471988,"score_gpt":0.2139351207148065,"score_spread":0.2076257396413345,"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."}}