{"id":"W4392602450","doi":"10.1089/jpm.2023.0675","title":"Can We Make More Accurate Prognoses During Last Days of Life?","year":2024,"lang":"en","type":"article","venue":"Journal of Palliative Medicine","topic":"Palliative Care and End-of-Life Issues","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"St Mary's Hospital Centre; McGill University; Computer Research Institute of Montréal; McGill University Health Centre; Université de Montréal; Merck Canada Inc. (Canada)","funders":"","keywords":"Medicine; Life expectancy; Palliative care; Survival analysis; Prospective cohort study; Receiver operating characteristic; Internal medicine; Intensive care medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.007950933,0.0008344055,0.00104596,0.002519343,0.0003981816,0.001873167,0.001138476,0.001029848,0.002531612],"category_scores_gemma":[0.04344122,0.0002393204,0.0007566541,0.001684771,0.0007378208,0.004484326,0.001004088,0.002145663,0.001696948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007433401,"about_ca_system_score_gemma":0.001656707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008793548,"about_ca_topic_score_gemma":0.01296518,"domain_scores_codex":[0.9981976,0.0009684993,0.0001999362,0.0001755597,0.0002831768,0.0001752447],"domain_scores_gemma":[0.9777388,0.009237148,0.005040787,0.001350967,0.005022036,0.001610195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002247791,0.0001365541,0.8049784,0.0003773143,0.0001380143,0.0001467581,0.0007486219,0.001339976,0.0002927235,0.0006302023,0.01458327,0.1764033],"study_design_scores_gemma":[0.00009489431,0.0009390982,0.9240106,0.002883225,0.000312213,0.001137214,0.006102708,0.00975615,0.001041438,0.01392411,0.0395286,0.0002697535],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8087747,0.04128116,0.05040592,0.07743682,0.002712662,0.0003312451,0.008845384,0.0009553853,0.009256856],"genre_scores_gemma":[0.9252967,0.01507656,0.04720763,0.004817197,0.001335595,0.0003109348,0.00472104,0.0001294157,0.001104918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008793548,"threshold_uncertainty_score":0.04204905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1215123174953824,"score_gpt":0.4221599087755042,"score_spread":0.3006475912801219,"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."}}