{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000305825,0.0001027215,0.0002820659,0.00004199183,0.0006513369,0.000004192529,0.0001276012,0.00003682334,0.0005016446],"category_scores_gemma":[0.00002828209,0.00007430816,0.00004799854,0.00003733748,0.00003972163,0.00006051303,0.00004882832,0.0002489062,0.0001864664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002921343,"about_ca_system_score_gemma":0.004005853,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9811407,"about_ca_topic_score_gemma":0.9873745,"domain_scores_codex":[0.9985865,0.0001417117,0.0006338571,0.000133594,0.00002446329,0.0004798452],"domain_scores_gemma":[0.998612,0.0006789026,0.0003255818,0.0002352552,0.00003434811,0.00011389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001216152,0.00001965568,0.9097401,0.00003506927,0.00002338773,1.184747e-7,0.0004165321,0.0002995367,3.759514e-7,0.004332717,0.08400536,0.001114997],"study_design_scores_gemma":[0.0003480394,0.00006457602,0.9918669,0.0000321486,8.873952e-7,1.347492e-7,0.001201621,0.0002459726,9.851424e-7,0.0021116,0.004063501,0.0000636449],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815701,0.0001187894,2.069092e-7,0.01141218,0.0004000145,0.0008374543,0.000123939,0.000008535336,0.005528776],"genre_scores_gemma":[0.9967257,0.0009240151,0.000003598328,0.001692096,0.00006109589,0.0001630774,0.00001502965,0.00001154949,0.0004038548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0821268,"threshold_uncertainty_score":0.7639211,"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."}}