{"id":"W7161979902","doi":"10.82308/11922","title":"How many fit all? Latent class analysis of administrative data on healthcare utilization by persons with dementia in Quebec, Canada","year":2022,"lang":"en","type":"dissertation","venue":"","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Latent class model; Dementia; Polypharmacy; Health care; Cohort; Descriptive statistics; Psychological intervention; Geriatrics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003255176,0.0003902997,0.0005207848,0.00192362,0.001847707,0.001902014,0.001246681,0.0004364971,0.00216087],"category_scores_gemma":[0.007881933,0.0002629381,0.001040304,0.004483829,0.0008809143,0.0005297594,0.0009449471,0.0007889734,0.0002752676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02052164,"about_ca_system_score_gemma":0.01817214,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9928743,"about_ca_topic_score_gemma":0.990766,"domain_scores_codex":[0.9982249,0.0004753606,0.0001457321,0.0002731339,0.0003544231,0.0005264989],"domain_scores_gemma":[0.9941317,0.001272969,0.001243289,0.0004789092,0.002155411,0.0007175771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006032949,0.00002676191,0.9946216,0.00002045467,0.00008372278,0.0000256678,0.0003790289,0.0005606812,0.00003878769,0.0002318305,0.001382824,0.002568207],"study_design_scores_gemma":[0.00001259894,0.00001939618,0.9882603,0.00005604588,0.00004066904,0.0000264476,0.001234793,0.009077745,0.00002881948,0.0001683741,0.001057928,0.00001692449],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978433,0.0007773396,0.001700092,0.0008848698,0.00002087472,0.0001497343,0.01635121,0.00003710345,0.001645763],"genre_scores_gemma":[0.9921576,0.000244037,0.0007346301,0.00007808676,0.000005930465,0.00004204016,0.006092868,0.000007332469,0.0006375234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02052164,"threshold_uncertainty_score":0.1488956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09832702048681838,"score_gpt":0.3929490236531242,"score_spread":0.2946220031663058,"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."}}