{"id":"W4391302647","doi":"10.1200/jco.2024.42.4_suppl.208","title":"Building a predictive model for outcomes with [177Lu]Lu-PSMA-617 in patients with metastatic castration-resistant prostate cancer using VISION data: Preliminary results.","year":2024,"lang":"en","type":"article","venue":"Journal of Clinical Oncology","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Medical Research Council; Novartis Pharmaceuticals Corporation","keywords":"Medicine; Prostate cancer; Oncology; Castration; Internal medicine; Cancer; Hormone","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":[],"consensus_categories":[],"category_scores_codex":[0.004593988,0.0008828596,0.0008230727,0.001263028,0.0002999039,0.001029675,0.0007687209,0.0005170063,0.002193226],"category_scores_gemma":[0.006844967,0.0002962541,0.001564176,0.0007212427,0.0002532085,0.0004307474,0.0005726031,0.00101079,0.000555269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001021712,"about_ca_system_score_gemma":0.001419114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01451783,"about_ca_topic_score_gemma":0.01103757,"domain_scores_codex":[0.9992042,0.0004110668,0.00004298011,0.0001713698,0.00008105719,0.00008939688],"domain_scores_gemma":[0.994595,0.004410294,0.0003565982,0.0001844292,0.0002467239,0.0002068892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003122421,0.00073468,0.7903416,0.0001048315,0.0008640015,0.0002997521,0.000180528,0.1366602,0.000733953,0.0003417399,0.002602732,0.06401351],"study_design_scores_gemma":[0.0001592702,0.001142934,0.1228623,0.00003958214,0.0004556105,0.0002517095,0.0001618651,0.8717126,0.0008307355,0.001151309,0.001194187,0.00003799016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9704373,0.0004687014,0.02392071,0.0004516243,0.00003319376,0.0001494398,0.003156037,0.0003308802,0.001052046],"genre_scores_gemma":[0.989823,0.000112067,0.006087468,0.00004478754,0.00002274229,0.00009739976,0.003267203,0.00002417729,0.0005210836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01451783,"threshold_uncertainty_score":0.02886671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2339183130763819,"score_gpt":0.5423661705284767,"score_spread":0.3084478574520948,"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."}}