{"id":"W4391946752","doi":"10.1002/soej.12684","title":"Economic fluctuations and mortality in Canada revisited","year":2024,"lang":"en","type":"article","venue":"Southern Economic Journal","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Margin (machine learning); Demographic economics; Economics; Panel data; Mortality rate; Demography; Aggregate data; Econometrics; Medicine","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":[0.0007477414,0.0002933407,0.0005919066,0.002925011,0.001431927,0.0020145,0.0007522344,0.0003200074,0.002947412],"category_scores_gemma":[0.003493758,0.0001976223,0.0005285696,0.008145709,0.000549994,0.0004255153,0.0009136865,0.0009495405,0.0002262179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02133931,"about_ca_system_score_gemma":0.02514373,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9959838,"about_ca_topic_score_gemma":0.9967068,"domain_scores_codex":[0.9993,0.00004756337,0.00003832036,0.00008494935,0.0002560514,0.0002731148],"domain_scores_gemma":[0.9970408,0.0002888647,0.0006649546,0.000104655,0.001524406,0.0003761466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007160959,0.00001860593,0.9809394,0.00004728909,0.0001132367,0.0001218757,0.0003981098,0.002878171,0.00009243906,0.001585401,0.004863684,0.008870312],"study_design_scores_gemma":[0.000003305026,0.00000668052,0.9925202,0.00005005284,0.00002628653,0.00002198083,0.0004469065,0.001288438,0.00009016183,0.0001570032,0.005376518,0.00001254999],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9317363,0.004772416,0.000507803,0.004671483,0.00007293305,0.00003229875,0.04502407,0.00006783018,0.01311475],"genre_scores_gemma":[0.9864267,0.001325491,0.0001693469,0.0001573279,0.00002313592,0.00000621889,0.00912757,0.000008677527,0.002755537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02133931,"threshold_uncertainty_score":0.1548283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03509567568643847,"score_gpt":0.3532821609427389,"score_spread":0.3181864852563004,"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."}}