{"id":"W2999856875","doi":"10.1016/j.mayocpiqo.2019.09.002","title":"Best Definitions of Multimorbidity to Identify Patients With High Health Care Resource Utilization","year":2020,"lang":"en","type":"article","venue":"Mayo Clinic Proceedings Innovations Quality & Outcomes","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"UniBern Forschungsstiftung; Mallinckrodt Pharmaceuticals; Portola Pharmaceuticals; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Medicine; Quartile; Comorbidity; Receiver operating characteristic; Cutoff; Cohort; Retrospective cohort study; Health care; Multimorbidity; Cohort study; Emergency medicine; Internal medicine; Confidence interval","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":[0.0004551472,0.0002600453,0.0006727832,0.0002957672,0.0002125119,0.00006242051,0.0002205857,0.00008349092,0.0002234588],"category_scores_gemma":[0.001877551,0.0002351916,0.0001099118,0.001999465,0.0001447354,0.0002614742,0.0001684435,0.0002462883,0.00007197252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002249798,"about_ca_system_score_gemma":0.0003723906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001840868,"about_ca_topic_score_gemma":0.00002516897,"domain_scores_codex":[0.9970353,0.00003352876,0.001332907,0.0005323793,0.0007511173,0.0003147807],"domain_scores_gemma":[0.9972388,0.0001343844,0.0006888598,0.0003017207,0.001406064,0.000230215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003192768,0.0009304029,0.9246536,0.002541745,0.0002410383,0.000001059021,0.004208371,0.00001011833,0.00002950363,0.05170749,0.01322476,0.002132657],"study_design_scores_gemma":[0.003205031,0.000746023,0.9807392,0.0002647983,0.0001642223,2.589475e-7,0.009183424,0.000008344008,0.00007170352,0.0002980591,0.005073181,0.0002457483],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9659494,0.00003290268,0.0006748932,0.02525363,0.00009312671,0.001628245,0.0003667464,0.0002292347,0.005771892],"genre_scores_gemma":[0.986069,0.00001464549,0.003868063,0.008559261,0.00007386975,0.00008644914,0.001157013,0.00003898049,0.0001327611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05608563,"threshold_uncertainty_score":0.9590833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2895928152753264,"score_gpt":0.4660031832023131,"score_spread":0.1764103679269867,"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."}}