{"id":"W6939955560","doi":"10.6084/m9.figshare.7285910","title":"Additional file 2: of Regional variation in healthcare spending and mortality among senior high-cost healthcare users in Ontario, Canada: a retrospective matched cohort study","year":2018,"lang":"en","type":"article","venue":"Figshare","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health care; Variation (astronomy); Retrospective cohort study; Regional variation; Statistical analysis; Cohort study; Statistical model; MEDLINE","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001198728,0.0006452242,0.001019222,0.002287062,0.00178545,0.001067993,0.00169434,0.0006325359,0.3423125],"category_scores_gemma":[0.01788303,0.0005512447,0.001756073,0.005245814,0.0003195306,0.0009593506,0.0007634265,0.0007999765,0.01085848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008120805,"about_ca_system_score_gemma":0.01654403,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9095732,"about_ca_topic_score_gemma":0.9226564,"domain_scores_codex":[0.9992257,0.0000678032,0.0001379083,0.0001318314,0.0002261966,0.0002104461],"domain_scores_gemma":[0.9888523,0.003964035,0.001295297,0.0008153511,0.004475374,0.000597671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003733649,0.00008011684,0.0837758,0.001358787,0.0002208296,0.0001031121,0.0002658991,0.0008385138,0.00007245432,0.0007191204,0.9054141,0.006777963],"study_design_scores_gemma":[0.003142422,0.0001835329,0.7921981,0.003695143,0.000675,0.0004138725,0.001723023,0.004533737,0.0004158465,0.001569569,0.1912597,0.0001901883],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.002173703,0.00002240912,0.00009013537,0.00009376708,0.00001337343,0.0000939135,0.9966275,0.00004083158,0.0008442752],"genre_scores_gemma":[0.1165996,0.0003188469,0.002737102,0.0006521372,0.00008679213,0.002720904,0.8543459,0.0002479297,0.0222908],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3423125,"threshold_uncertainty_score":0.9381115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06331864603359987,"score_gpt":0.3697274218434582,"score_spread":0.3064087758098584,"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."}}