{"id":"W2090953687","doi":"10.1021/ci900219u","title":"Evaluation of Virtual Screening as a Tool for Chemical Genetic Applications","year":2009,"lang":"en","type":"article","venue":"Journal of Chemical Information and Modeling","topic":"Protein Degradation and Inhibitors","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Structural Genomics Consortium; University of Toronto","funders":"Wellcome Trust","keywords":"Virtual screening; In silico; Computational biology; Biology; Gene; Function (biology); Acetylation; Genetics; Bioinformatics; Drug discovery","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002870147,0.00107018,0.001024484,0.001092394,0.0003832423,0.001337929,0.001065967,0.0006341822,0.002496338],"category_scores_gemma":[0.005038914,0.0003107349,0.0005205584,0.001014028,0.0005776726,0.0006875094,0.0009252831,0.000449364,0.0004896512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007055952,"about_ca_system_score_gemma":0.0007678926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001327295,"about_ca_topic_score_gemma":0.0007546541,"domain_scores_codex":[0.9981299,0.001130148,0.00005703873,0.0001098289,0.0004790463,0.00009406574],"domain_scores_gemma":[0.9977581,0.001654099,0.00009241165,0.0001738968,0.0002396587,0.00008190693],"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":[0.001945443,0.0006789379,0.004172617,0.0003514318,0.0002361612,0.0005570601,0.0001308817,0.8253846,0.02923276,0.01692295,0.003723016,0.1166643],"study_design_scores_gemma":[0.0001613246,0.000577332,0.0005302524,0.00001252863,0.00004904826,0.0001230746,0.00003096882,0.9746128,0.01763537,0.003395632,0.002849374,0.00002232139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6601278,0.00116893,0.2965895,0.0009771582,0.0001330331,0.0007974218,0.001955045,0.01463018,0.02362082],"genre_scores_gemma":[0.8999586,0.0004124447,0.09684909,0.0001141011,0.00001299685,0.0003328022,0.000756055,0.0002118547,0.001352118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002870147,"threshold_uncertainty_score":0.01517892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02470413877491048,"score_gpt":0.3010721495933626,"score_spread":0.2763680108184521,"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."}}