{"id":"W2059097089","doi":"10.1021/jm201098n","title":"Targeting the Binding Function 3 (BF3) Site of the Human Androgen Receptor through Virtual Screening.","year":2011,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":147,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; Canadian Institutes of Health Research","keywords":"Androgen receptor; In silico; Mechanism of action; Virtual screening; Prostate cancer; Chemistry; Antiandrogen; Mechanism (biology); Computational biology; Cytotoxicity; Function (biology); Androgen; Drug; Binding site; Drug discovery; Pharmacology; Cancer research; Cancer; Biochemistry; Biology; In vitro; Cell biology; Genetics; 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":[0.000699773,0.0001166253,0.0002589881,0.00002657893,0.0001789856,0.000006623473,0.0001833856,0.00008393163,0.0008558408],"category_scores_gemma":[0.0001743126,0.000053398,0.0001715701,0.0001867961,0.0002587473,0.00008406613,0.0000570039,0.0006009086,0.000002934004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000831397,"about_ca_system_score_gemma":0.000156647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002063774,"about_ca_topic_score_gemma":3.199307e-7,"domain_scores_codex":[0.998535,0.00004397423,0.0004271615,0.0001024277,0.0006935036,0.0001979109],"domain_scores_gemma":[0.9989564,0.00006159172,0.0004580742,0.0001785091,0.0002462397,0.00009915306],"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":[0.001102443,0.0001314484,0.05568499,0.0001502497,0.0003612317,0.00004852454,0.00241539,0.000002534621,0.9317394,0.00000977727,0.006167267,0.002186754],"study_design_scores_gemma":[0.003922931,0.001027632,0.009782953,0.001220501,0.0005420005,0.0004384928,0.006436937,0.00001658707,0.9683521,0.00007992981,0.008069918,0.0001099785],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935273,0.001876265,0.0001256334,0.0008488114,0.0002096836,0.0001149427,0.000005408594,0.000006069489,0.003285869],"genre_scores_gemma":[0.9969289,0.0002172761,0.0001962461,0.000103296,0.000865454,0.000002272194,0.000008111167,0.00001431412,0.001664154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04590204,"threshold_uncertainty_score":0.9370856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04831820523702504,"score_gpt":0.3040674497260342,"score_spread":0.2557492444890092,"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."}}