{"id":"W2195839185","doi":"10.1111/cbdd.12697","title":"A New, Improved Hybrid Scoring Function for Molecular Docking and Scoring Based on AutoDock and AutoDock Vina","year":2015,"lang":"en","type":"article","venue":"Chemical Biology & Drug Design","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"National Academy of Sciences of Ukraine; Ontario Institute for Cancer Research","keywords":"AutoDock; Docking (animal); Computer science; Chemistry; In silico; Medicine; Biochemistry; Veterinary 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002489593,0.001483995,0.002609687,0.001899388,0.0006462446,0.001080856,0.002263819,0.0008012371,0.003242701],"category_scores_gemma":[0.002437772,0.0006926661,0.001334937,0.002272108,0.0003038105,0.001285531,0.001127028,0.001627347,0.002044931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00086535,"about_ca_system_score_gemma":0.001202258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003682319,"about_ca_topic_score_gemma":0.002915613,"domain_scores_codex":[0.9982835,0.0004846995,0.0001295225,0.0002244159,0.0007203182,0.0001576518],"domain_scores_gemma":[0.9990278,0.0002662016,0.00007503937,0.0001312888,0.0004376597,0.000061979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001252961,0.0006052702,0.008186763,0.001153243,0.001158472,0.0005555797,0.0001671328,0.09983572,0.08090069,0.01075595,0.05047467,0.7449536],"study_design_scores_gemma":[0.0004273083,0.0004809871,0.006928699,0.00006825044,0.0002404026,0.001312909,0.00003681863,0.849282,0.05645044,0.003287164,0.08108484,0.0004001705],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05277199,0.003426494,0.9198617,0.0002435596,0.0002531351,0.0002077827,0.001923704,0.01817816,0.003133439],"genre_scores_gemma":[0.2442119,0.002162058,0.7264341,0.000350974,0.0001164196,0.0008318641,0.01072499,0.002465874,0.01270186],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003682319,"threshold_uncertainty_score":0.01316643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04666427712497721,"score_gpt":0.3115320440287999,"score_spread":0.2648677669038227,"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."}}