{"id":"W4362543093","doi":"10.1158/2159-8290.22528656.v1","title":"Supplementary Figures 1-15, Supplementary Tables 1-2, Supplementary Methods from Molecular Characterization of Neuroendocrine Prostate Cancer and Identification of New Drug Targets","year":2023,"lang":"en","type":"supplementary-materials","venue":"","topic":"Estrogen and related hormone effects","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Identification (biology); Prostate cancer; Drug; Computational biology; Cancer; Medicine; Internal medicine; Pharmacology; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002075235,0.002226926,0.001663752,0.003392461,0.001814782,0.002705482,0.003782718,0.001608015,0.8724732],"category_scores_gemma":[0.01205191,0.001760527,0.001567134,0.004286,0.0005982863,0.002649103,0.001426104,0.002794944,0.581975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001762537,"about_ca_system_score_gemma":0.003625766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007904008,"about_ca_topic_score_gemma":0.01751943,"domain_scores_codex":[0.9985337,0.0001843786,0.0001335839,0.0003182634,0.0006459396,0.0001841702],"domain_scores_gemma":[0.9922153,0.004005327,0.0003699614,0.001015118,0.001642854,0.0007514606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001511875,0.00008042604,0.0002322061,0.001028948,0.00002354335,0.0000410943,0.00001871898,0.0003591115,0.001455551,0.001504112,0.9832941,0.01181097],"study_design_scores_gemma":[0.0003324821,0.0001059749,0.002776769,0.0003193087,0.00004373112,0.0002056745,0.00004976754,0.0006579626,0.005072486,0.004835344,0.9855414,0.00005906498],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002828229,0.0003285089,0.004775244,0.0003782038,0.0008241007,0.0001838567,0.9756573,0.002720295,0.01484968],"genre_scores_gemma":[0.002228716,0.0006749904,0.00935984,0.0005079981,0.0002289688,0.0006978113,0.9484969,0.003314155,0.03449067],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8724732,"threshold_uncertainty_score":0.1819014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007710040372996122,"score_gpt":0.2948716012976739,"score_spread":0.2871615609246778,"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."}}