{"id":"W1749785499","doi":"10.24095/hpcdp.34.4.05","title":"Multimorbidity disease clusters in Aboriginal and non-Aboriginal Caucasian populations in Canada","year":2014,"lang":"en","type":"article","venue":"Chronic diseases and injuries in Canada","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Manitoba Health Research Council","keywords":"Demography; Medicine; Cluster (spacecraft); Population; Chronic disease; Disease; Latent class model; Community health; Multimorbidity; Ethnic group; Gerontology; Public health; Environmental health; Family medicine; Internal medicine; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001056241,0.000321961,0.0005159705,0.002064751,0.003354477,0.001229501,0.001021918,0.0003424012,0.001073288],"category_scores_gemma":[0.001980349,0.0003137271,0.0004864316,0.004257833,0.0009044562,0.000325754,0.001296355,0.0004908938,0.0001227536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01574772,"about_ca_system_score_gemma":0.02263411,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9912826,"about_ca_topic_score_gemma":0.9934381,"domain_scores_codex":[0.9989702,0.0001188523,0.0000565686,0.0002110705,0.0002925085,0.0003508668],"domain_scores_gemma":[0.9986325,0.00008973169,0.0003123056,0.00005063052,0.0005243138,0.0003906021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007387486,0.0000180597,0.9919794,0.00005167354,0.00006337662,0.0001010711,0.002661503,0.00008991371,0.0002436193,0.00009495412,0.0005423951,0.004080166],"study_design_scores_gemma":[0.000003763115,0.00001474837,0.9975792,0.00002467656,0.0000174515,0.00004871098,0.001788437,0.0001467912,0.00002620488,0.0000364417,0.0003073284,0.000006281457],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971868,0.000605008,0.00009892491,0.0001746827,0.000006389152,0.00003445665,0.001008779,0.000006880613,0.0008780471],"genre_scores_gemma":[0.9984277,0.0003559285,0.0001986811,0.00005585858,0.000003621143,0.00001859975,0.0006726964,0.000003140111,0.0002639195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01574772,"threshold_uncertainty_score":0.1142582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01265151142150913,"score_gpt":0.3014430975253932,"score_spread":0.2887915861038841,"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."}}