{"id":"W3151307685","doi":"10.3386/w15163","title":"Does Health Insurance Make You Fat?","year":2009,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Services and Policy Research","funders":"","keywords":"Health insurance; Business; Actuarial science; Economics; Health care; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001556691,0.0001553923,0.0004188079,0.0007489506,0.0005082018,0.001390819,0.0003566074,0.001198447,0.0115997],"category_scores_gemma":[0.01549855,0.0001762463,0.0003481484,0.0009776489,0.001474513,0.001455946,0.0006399411,0.001441566,0.0008133837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006424335,"about_ca_system_score_gemma":0.0005417619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007949467,"about_ca_topic_score_gemma":0.006571738,"domain_scores_codex":[0.9993097,0.0002911557,0.00003293098,0.00008557375,0.0001558617,0.0001249381],"domain_scores_gemma":[0.9882178,0.006885541,0.003486346,0.0004572573,0.0003774183,0.0005756682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006446005,0.0004005231,0.8163095,0.0002182327,0.000330061,0.0002694282,0.001476754,0.0008260125,0.0002530496,0.03469485,0.03124795,0.113329],"study_design_scores_gemma":[0.0001618945,0.0002039287,0.8865373,0.0004345172,0.0003475229,0.0004005304,0.003632203,0.002591486,0.0003915747,0.05624263,0.04901776,0.00003862768],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8065416,0.01385002,0.001768546,0.139981,0.0006227179,0.00005298591,0.003528336,0.00005311062,0.03360165],"genre_scores_gemma":[0.9900246,0.002911543,0.0002641629,0.003652028,0.0004381715,0.00001949321,0.0005260392,0.000007336787,0.002156677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0115997,"threshold_uncertainty_score":0.03880483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3929797957899476,"score_gpt":0.503062760555583,"score_spread":0.1100829647656353,"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."}}