{"id":"W2036976345","doi":"10.1021/ci300514v","title":"Identification of Novel Androgen Receptor Antagonists Using Structure- and Ligand-Based Methods","year":2013,"lang":"en","type":"article","venue":"Journal of Chemical Information and Modeling","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Bicalutamide; Androgen receptor; Antiandrogens; Enzalutamide; Prostate cancer; Virtual screening; Computational biology; Chemistry; Drug discovery; Pharmacology; Combinatorial chemistry; Biology; Cancer; Medicine; Biochemistry; Internal 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":[0.0006093848,0.00007121819,0.0001554639,0.0001445531,0.00003368782,0.0001685937,0.0001446065,0.00004875378,0.000001874044],"category_scores_gemma":[0.0001569426,0.00006056267,0.00003836969,0.0001269851,0.00002802308,0.002082558,0.00005757899,0.00009997375,1.904941e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002583723,"about_ca_system_score_gemma":0.0000864992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005649501,"about_ca_topic_score_gemma":1.850851e-8,"domain_scores_codex":[0.9989339,0.00003531596,0.0006894234,0.00006141129,0.0002057277,0.00007424653],"domain_scores_gemma":[0.9988241,0.0001097676,0.0004935007,0.00007962261,0.0004201602,0.00007284987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000121114,0.00001568274,0.00002360941,0.00005326362,0.00001400493,4.188637e-8,0.0005067671,0.1654385,0.8028953,0.001268573,0.0000100264,0.02976215],"study_design_scores_gemma":[0.0002806468,0.000008817264,0.0000125975,0.00002396884,0.000005849148,0.0000257295,0.00002232492,0.7186521,0.2792304,0.001678037,0.00001360062,0.00004600129],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4764465,0.00003417486,0.5233003,0.0001130698,0.00006350395,0.00003491176,0.000001606124,0.000003202564,0.000002738048],"genre_scores_gemma":[0.5607709,0.00000572102,0.4391299,0.0000724207,0.00001766482,3.207589e-7,0.0000014402,0.000001451596,1.758247e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5532136,"threshold_uncertainty_score":0.2469674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04240487230861293,"score_gpt":0.3452276244742843,"score_spread":0.3028227521656713,"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."}}