{"id":"W2154236811","doi":"10.1177/1087057108315881","title":"Using the Protein Chip to Screen Agonists and Antagonists of the Androgen Receptor","year":2008,"lang":"en","type":"article","venue":"SLAS DISCOVERY","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"National High-tech Research and Development Program; University of Ottawa","keywords":"Androgen receptor; Receptor; Agonist; Pharmacology; Chemistry; Biology; Internal medicine; Medicine; Biochemistry; Cancer; Prostate cancer","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":[0.00005202235,0.00008230355,0.00007264285,0.00000874744,0.0002055387,0.00001380081,0.0001470276,0.00004823124,8.404504e-7],"category_scores_gemma":[0.0000234122,0.00004893625,0.00004797746,0.00008562393,0.0001990371,0.000004323772,0.0001752501,0.00004751005,5.585148e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006915312,"about_ca_system_score_gemma":0.00004533173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000286996,"about_ca_topic_score_gemma":0.00001452477,"domain_scores_codex":[0.9995144,0.00002458149,0.0001042443,0.0001732653,0.0000730547,0.0001104566],"domain_scores_gemma":[0.9995253,0.000003980115,0.00006058711,0.0003564233,0.00002759453,0.00002612626],"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":[0.00002227111,0.00001641177,0.001072713,0.000003879801,0.000009936569,2.364275e-7,0.00002259142,0.0000102843,0.9974084,0.0007566877,0.00041523,0.0002613936],"study_design_scores_gemma":[0.000081834,0.00005220787,0.00168024,0.00001982856,0.000006188503,0.00002595961,0.00001937267,0.00001332369,0.9784446,0.0002682387,0.01930338,0.00008481932],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932287,0.0001495518,0.005547924,0.0004623056,0.00002089723,0.0003900156,0.0000559223,0.000007257482,0.0001374734],"genre_scores_gemma":[0.9924524,0.00005098868,0.006786314,0.0002017424,0.00007550319,0.00001359009,0.00001317744,0.00001157361,0.0003947028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01896375,"threshold_uncertainty_score":0.1995563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0230399087295452,"score_gpt":0.2797386675944851,"score_spread":0.2566987588649399,"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."}}