{"id":"W1840780240","doi":"10.1002/hec.2946","title":"THE IMPACT OF MACROECONOMIC CONDITIONS ON OBESITY IN CANADA","year":2013,"lang":"en","type":"article","venue":"Health Economics","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Unemployment; Economics; Logit; Overweight; Obesity; Unemployment rate; Demographic economics; Fixed effects model; Econometrics; Population; Panel data; Demography; Medicine; Macroeconomics; Sociology; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0009363145,0.00027057,0.0004292823,0.001905402,0.002099882,0.001802748,0.0006231557,0.0003745004,0.002612716],"category_scores_gemma":[0.004084026,0.0002667606,0.00101479,0.003828062,0.0005093903,0.0003940529,0.001183995,0.001109606,0.000154111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03794035,"about_ca_system_score_gemma":0.053595,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9979906,"about_ca_topic_score_gemma":0.998368,"domain_scores_codex":[0.9990802,0.00009330157,0.00004525136,0.0000880517,0.0002379878,0.0004552434],"domain_scores_gemma":[0.9972928,0.0002864454,0.0004976057,0.0000813722,0.001131324,0.0007103785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001305309,0.00004074877,0.9870863,0.00004681986,0.0001790593,0.0001542537,0.0002982661,0.001549959,0.00008551378,0.0009240898,0.002245981,0.007258426],"study_design_scores_gemma":[0.000008303701,0.00001298592,0.9965133,0.00003817019,0.00006011379,0.00002482276,0.0004846547,0.001234503,0.00004254794,0.0001153674,0.00145157,0.00001374648],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9730223,0.003691999,0.0002064179,0.002814164,0.00006584587,0.00003156396,0.01413948,0.00002149738,0.006006679],"genre_scores_gemma":[0.9951924,0.001338843,0.000134535,0.000125952,0.00001192489,0.000007693861,0.002066805,0.000004612961,0.001117242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03794035,"threshold_uncertainty_score":0.2752778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03992412209543529,"score_gpt":0.3909486640441582,"score_spread":0.3510245419487229,"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."}}