{"id":"W3198605523","doi":"10.1093/jamia/ocab140","title":"Expected clinical utility of automatable prediction models for improving palliative and end-of-life care outcomes: Toward routine decision analysis before implementation","year":2021,"lang":"en","type":"article","venue":"Journal of the American Medical Informatics Association","topic":"Palliative Care and End-of-Life Issues","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Palliative care; End-of-life care; Medicine; Computer science; Intensive care medicine; Nursing","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":[0.05845185,0.00177574,0.001466067,0.002178908,0.000402435,0.00333291,0.001887508,0.001768925,0.001086373],"category_scores_gemma":[0.2446755,0.0008154219,0.001064952,0.00112784,0.001145495,0.003112322,0.001464185,0.002564881,0.0002517464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00197629,"about_ca_system_score_gemma":0.003029166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003630986,"about_ca_topic_score_gemma":0.002460247,"domain_scores_codex":[0.9621942,0.03017398,0.001601747,0.002297119,0.00323602,0.0004970615],"domain_scores_gemma":[0.6931716,0.281391,0.009646471,0.006050486,0.008518515,0.001221981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002814806,0.001005112,0.2169221,0.0003521319,0.001343414,0.0002409194,0.0002701007,0.6655908,0.001009093,0.004300599,0.002200133,0.1039508],"study_design_scores_gemma":[0.00009975457,0.0004912628,0.004590371,0.00007685512,0.00009281333,0.00005245734,0.00005095159,0.9885396,0.0005925368,0.005197053,0.0001891582,0.00002725843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5650299,0.001565937,0.4219831,0.004867814,0.0001751467,0.0008387705,0.000799015,0.001330751,0.003409576],"genre_scores_gemma":[0.9277207,0.0001597651,0.07106739,0.0003606045,0.00005531294,0.000199543,0.000260421,0.00003265294,0.0001436097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05845185,"threshold_uncertainty_score":0.3091266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08730913357338663,"score_gpt":0.4557360731797833,"score_spread":0.3684269396063967,"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."}}