{"id":"W2553944050","doi":"10.1021/acs.jcim.6b00400","title":"Cheminformatics Modeling of Adverse Drug Responses by Clinically Relevant Mutants of Human Androgen Receptor","year":2016,"lang":"en","type":"article","venue":"Journal of Chemical Information and Modeling","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Cancer Institute; Canadian Cancer Society Research Institute","keywords":"Androgen receptor; Enzalutamide; Cheminformatics; Antiandrogens; Computational biology; Prostate cancer; Mutant; In silico; Bicalutamide; DrugBank; Transcription factor; Drug repositioning; Drug; Biology; Bioinformatics; Chemistry; Medicine; Genetics; Pharmacology; Cancer; Gene","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":[0.0006748756,0.0000943993,0.0003565934,0.0001340032,0.00002495923,0.000005320361,0.00007895807,0.00008664182,0.00002426874],"category_scores_gemma":[0.0003647803,0.00005540453,0.0001144797,0.00007063524,0.00007201335,0.0006161306,0.00003903681,0.0001564517,0.000001503671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006061552,"about_ca_system_score_gemma":0.0001648926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003031607,"about_ca_topic_score_gemma":3.926559e-8,"domain_scores_codex":[0.9979579,0.00001145327,0.001445202,0.00004551748,0.0004025133,0.000137427],"domain_scores_gemma":[0.9984601,0.00008714934,0.000556996,0.000100797,0.000633456,0.0001615737],"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":[0.00793301,0.0002174034,0.001156642,0.000813507,0.0002774857,0.000002904391,0.003986341,0.0005261733,0.9636429,0.0000666569,0.001210571,0.02016642],"study_design_scores_gemma":[0.009175174,0.0006812918,0.000005092255,0.002083014,0.0001487119,0.00007550165,0.001747918,0.2107161,0.7744898,0.0003745378,0.0003288574,0.0001739736],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955382,0.000217044,0.003312057,0.0004228902,0.00002764429,0.0001149587,0.00002852992,0.000005826585,0.0003328453],"genre_scores_gemma":[0.996496,0.001362136,0.001973393,0.00006500478,0.00003030598,0.000001286669,0.00001353997,0.000005716935,0.000052673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.21019,"threshold_uncertainty_score":0.2259331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04440772685249501,"score_gpt":0.3498515790777051,"score_spread":0.3054438522252101,"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."}}