{"id":"W4403537585","doi":"10.1016/j.esmoop.2024.103818","title":"77P Elucidating molecularly stratified single agent, and combination, therapeutic strategies targeting MCL1 for lethal prostate cancer","year":2024,"lang":"en","type":"article","venue":"ESMO Open","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"DOD Prostate Cancer Research Program; National Cancer Institute; Medical Research Council; Genentech; Sierra Oncology; Astellas Pharma; Eisai; Prostate Cancer UK; Cancer Research UK; National Center for Advancing Translational Sciences; Wellcome Trust; Prostate Cancer Foundation; Bristol-Myers Squibb; AstraZeneca; Movember Foundation; Daiichi Sankyo Europe; U.S. Department of Defense; Sanofi; Amgen; Pfizer; Vertex Pharmaceuticals; National Institutes of Health; Menarini Silicon Biosystems","keywords":"Prostate cancer; MCL1; Cancer; Medicine; Prostate; Cancer research; Internal medicine; Biology; Genetics; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003345527,0.0001422063,0.0001933539,0.00006647208,0.0001881203,0.0007655466,0.0001110829,0.0000440848,0.0001064637],"category_scores_gemma":[0.00002627364,0.0001077817,0.00004116746,0.0001585383,0.0000734762,0.0004191851,0.00007742471,0.0001494183,0.000005415684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001025456,"about_ca_system_score_gemma":0.0004210188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006322011,"about_ca_topic_score_gemma":0.00006901199,"domain_scores_codex":[0.9989635,0.00004278421,0.0001915771,0.0003359012,0.0001797193,0.0002865515],"domain_scores_gemma":[0.999559,0.00008358368,0.00003853388,0.0001203369,0.0001165553,0.0000819554],"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":[0.002343137,0.001005774,0.01357763,0.004628353,0.002683571,0.0009331469,0.01957653,0.00008824799,0.5707349,0.04331934,0.01015479,0.3309546],"study_design_scores_gemma":[0.02519767,0.006510245,0.03249817,0.004381843,0.001328877,0.0001586139,0.0222016,0.0193239,0.7424018,0.04441306,0.09961891,0.001965292],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9405072,0.01907242,0.002986133,0.01391523,0.0006013887,0.007130413,0.000142439,0.0002214974,0.0154233],"genre_scores_gemma":[0.993104,0.0002130244,0.0007819472,0.000145806,0.00008021294,0.0004982842,0.0001922665,0.00003730876,0.004947179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3289893,"threshold_uncertainty_score":0.7382183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0645400951627398,"score_gpt":0.3920523083365812,"score_spread":0.3275122131738414,"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."}}