{"id":"W4394606203","doi":"10.1158/2159-8290.cd-23-0539","title":"ZNF397 Deficiency Triggers TET2-Driven Lineage Plasticity and AR-Targeted Therapy Resistance in Prostate Cancer","year":2024,"lang":"en","type":"article","venue":"Cancer Discovery","topic":"Cancer-related gene regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"National Institute of General Medical Sciences; Cancer Prevention and Research Institute of Texas; Terry Fox Foundation; Welch Foundation; National Cancer Institute; Prostate Cancer Foundation; Life Sciences Research Foundation; U.S. Department of Defense","keywords":"Prostate cancer; Lineage (genetic); Cancer; Cancer research; Prostate; Biology; Resistance (ecology); Medicine; Bioinformatics; Internal medicine; 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":[0.00008406007,0.0002083336,0.0001799889,0.00008873904,0.00006066747,0.00009883796,0.0001070263,0.0001272723,0.00002994454],"category_scores_gemma":[0.00002013692,0.0001898661,0.00006880182,0.0003115442,0.00012411,0.00003196362,0.00004621709,0.0001545805,0.000002268055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001651033,"about_ca_system_score_gemma":0.0004394843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002611687,"about_ca_topic_score_gemma":0.002927899,"domain_scores_codex":[0.998673,0.00004187065,0.0002471545,0.0005848905,0.0001491725,0.000303949],"domain_scores_gemma":[0.9996303,0.00002199107,0.00006517201,0.0001812866,0.00004107399,0.00006015454],"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":[0.001238031,0.00008868281,0.0178606,0.0003254858,0.0001597138,0.00002352158,0.0007175017,0.01784571,0.9432165,0.0001603478,0.004930211,0.01343368],"study_design_scores_gemma":[0.003676289,0.0003553732,0.1181369,0.001188625,0.000106813,0.000009390118,0.0001853031,0.004495283,0.7393122,0.0003353016,0.1308629,0.001335624],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9014721,0.09649548,0.0003173175,0.0003234148,0.0005313114,0.0003450764,0.0002320033,0.00002674134,0.0002565908],"genre_scores_gemma":[0.9695029,0.02732574,0.00005956918,0.00009771217,0.0003159343,0.0001925413,0.00006889126,0.00003908352,0.002397614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2039043,"threshold_uncertainty_score":0.7742515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008218091518307867,"score_gpt":0.2601282679845754,"score_spread":0.2519101764662675,"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."}}