{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004379156,0.000225454,0.000351398,0.000109938,0.00008549185,0.0000281406,0.00008639845,0.0001184362,0.00001313251],"category_scores_gemma":[0.0004027474,0.000180185,0.00007583512,0.00009017141,0.0001215731,0.00004651379,0.00008898097,0.0002869654,0.000007250752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000707981,"about_ca_system_score_gemma":0.0001812506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006631759,"about_ca_topic_score_gemma":5.266716e-7,"domain_scores_codex":[0.9986013,0.00007043631,0.0002279473,0.0005169589,0.000138839,0.0004444981],"domain_scores_gemma":[0.9987862,0.0004230129,0.00005764286,0.0001842415,0.00009840758,0.000450478],"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":[0.003310272,0.00005977669,0.003047379,0.0001336186,0.00007822724,0.00002845121,0.00005168155,0.00005275736,0.9562305,0.0003328969,0.001407747,0.0352667],"study_design_scores_gemma":[0.004517329,0.001553899,0.0007077646,0.000218003,0.0001352556,0.00009489561,0.0000314906,0.09678609,0.885973,0.003867642,0.005744897,0.0003697569],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9422207,0.001167283,0.05322271,0.002070875,0.0001697913,0.0007056108,0.000008510203,0.00009343016,0.0003410708],"genre_scores_gemma":[0.9859282,0.00002668507,0.01262972,0.0007217102,0.0003067178,0.00005198428,0.00004524994,0.00002843483,0.0002613218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09673333,"threshold_uncertainty_score":0.734773,"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."}}