{"id":"W7127290159","doi":"10.1111/caje.70041","title":"Economic activity during extreme events","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Natural disaster; Extreme weather; Economic data; Natural (archaeology); Economic impact analysis; Extreme heat; Database transaction","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0006451784,0.0001410238,0.000205565,0.001615009,0.0003638727,0.001503877,0.0002676234,0.0003652688,0.005047092],"category_scores_gemma":[0.00525539,0.00007326825,0.0001759565,0.002765875,0.0003961767,0.0007497436,0.0009294288,0.0006329037,0.0009475188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008142588,"about_ca_system_score_gemma":0.0003849627,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02450457,"about_ca_topic_score_gemma":0.03104186,"domain_scores_codex":[0.9994845,0.0001881002,0.00003718771,0.00005712862,0.0001303464,0.0001026308],"domain_scores_gemma":[0.9969774,0.0008157126,0.00105265,0.0001490153,0.000582078,0.0004231183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003189042,0.0001417333,0.8497323,0.0005884084,0.0002657367,0.0008035127,0.003372827,0.006256796,0.0007751393,0.01385084,0.03954962,0.08434413],"study_design_scores_gemma":[0.000005427451,0.00005497483,0.9453055,0.0002563989,0.00002264135,0.0001797047,0.004592032,0.00164083,0.0002439294,0.003072682,0.04459791,0.00002785433],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8770981,0.004049282,0.002469514,0.005610489,0.0002819645,0.00007711766,0.02576994,0.00006013128,0.08458338],"genre_scores_gemma":[0.9888396,0.002582022,0.0003205896,0.0001685805,0.0001346596,0.00002346866,0.005144867,0.00001118716,0.002775118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9754954,"threshold_uncertainty_score":0.04872388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.104390475493585,"score_gpt":0.2186043112177594,"score_spread":0.1142138357241744,"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."}}