{"id":"W2914328904","doi":"10.12927/hcq.2018.25709","title":"Putting a Population Health Lens to Multimorbidity in Ontario","year":2018,"lang":"en","type":"article","venue":"Healthcare Quarterly","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Population and Public Health; Public Health Ontario","funders":"","keywords":"Health care; Multimorbidity; Equity (law); Medicine; Chronic disease; Population; Population health; Chronic condition; Disease management; Disease; Health equity; Healthcare system; Family medicine; Gerontology; Public health; Environmental health; Nursing; Health management system; Alternative medicine; Economic growth; Pathology; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.002109137,0.0001629547,0.0003132665,0.001322109,0.005564331,0.002311921,0.001161648,0.0006888289,0.005654356],"category_scores_gemma":[0.004700475,0.0002815574,0.0003976924,0.002770571,0.001926208,0.001085018,0.002759166,0.001252732,0.0001615674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09396941,"about_ca_system_score_gemma":0.1193734,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9918953,"about_ca_topic_score_gemma":0.9963833,"domain_scores_codex":[0.9981019,0.0002840205,0.00009882097,0.0001177698,0.0006185814,0.0007788581],"domain_scores_gemma":[0.9964522,0.0003369265,0.0003400741,0.0001287917,0.0009713009,0.00177067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001765675,0.0002156106,0.5463853,0.0007159025,0.0001569762,0.001163312,0.05155992,0.001061623,0.001035362,0.0973242,0.1226506,0.1775546],"study_design_scores_gemma":[0.00003743705,0.00007762168,0.7620062,0.0004987913,0.00006950183,0.0002263098,0.01715105,0.0007408087,0.0002324143,0.007864534,0.2110331,0.00006224023],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5342054,0.01456259,0.002649047,0.2541577,0.0006368304,0.0003410507,0.004713042,0.0001435704,0.1885907],"genre_scores_gemma":[0.9710408,0.004862397,0.001715181,0.007372107,0.0001996874,0.0001278696,0.000492433,0.00003661597,0.01415298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09396941,"threshold_uncertainty_score":0.681799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08332643156329926,"score_gpt":0.3805400590323217,"score_spread":0.2972136274690224,"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."}}