{"id":"W1999519914","doi":"10.1021/ci200598m","title":"Numerical Errors and Chaotic Behavior in Docking Simulations","year":2012,"lang":"en","type":"article","venue":"Journal of Chemical Information and Modeling","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Ontario Institute for Cancer Research","funders":"","keywords":"Docking (animal); Virtual screening; Protein–ligand docking; Computer science; Chaotic; Algorithm; Artificial intelligence; Molecular dynamics; Chemistry; Computational chemistry; Medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000356288,0.00005255482,0.000101501,0.0001510735,0.00002451402,0.00006978834,0.00008409275,0.00003156797,0.000001568897],"category_scores_gemma":[0.0001168659,0.00004629216,0.00002375288,0.0001223738,0.00001020782,0.002936905,0.00005525687,0.0001407987,5.645155e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003056749,"about_ca_system_score_gemma":0.00002812164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002774006,"about_ca_topic_score_gemma":5.536778e-8,"domain_scores_codex":[0.9992725,0.00002240024,0.0003966516,0.00003396894,0.000168284,0.0001062356],"domain_scores_gemma":[0.9995509,0.0001039031,0.0001296478,0.00004268162,0.00007660918,0.00009619892],"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":[0.00001217048,0.00005013737,0.003223625,0.00001988918,0.000005629304,7.667574e-7,0.003284778,0.9489897,0.0008186362,0.005994799,0.000005500179,0.03759439],"study_design_scores_gemma":[0.000222163,0.000008347043,0.0008646358,0.00001897673,0.000004345793,0.00007236082,0.00004391478,0.9973078,0.0003581708,0.001002323,0.00004337225,0.00005362086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.559215,0.00006296367,0.4404652,0.0001508075,0.00005158031,0.00002167025,1.906159e-7,0.000003787701,0.00002880452],"genre_scores_gemma":[0.953382,0.000007545448,0.04642206,0.0001497826,0.00003544916,6.895242e-7,8.247708e-7,0.000001463767,2.343967e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3941669,"threshold_uncertainty_score":0.2129185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05000159485368189,"score_gpt":0.3394582415320608,"score_spread":0.2894566466783789,"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."}}