{"id":"W4412408599","doi":"10.1007/s42650-025-00093-9","title":"COVID-19, Excess Deaths, and Mortality: Evidence from a Municipality in Brazil","year":2025,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Coronavirus disease 2019 (COVID-19); Excess mortality; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Geography; Socioeconomics; Demography; Environmental health; Virology; Population; Medicine; Economics; Sociology; Outbreak; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009215288,0.0001281817,0.0004003775,0.0006462521,0.000118502,0.00003422534,0.000146595,0.0001082436,0.0000360678],"category_scores_gemma":[0.006911065,0.0001671512,0.00002693712,0.0005694953,0.00008943565,0.0002690714,0.00008004134,0.0001451955,0.000006940159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003020515,"about_ca_system_score_gemma":0.0002776835,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9175326,"about_ca_topic_score_gemma":0.9629131,"domain_scores_codex":[0.998636,0.00005159611,0.0005647865,0.0004165428,0.00003086917,0.000300184],"domain_scores_gemma":[0.998923,0.0003950329,0.0001291154,0.0003195177,0.00001661303,0.0002167245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006197682,0.000005510783,0.9829312,0.0000779748,0.0000301833,0.00001347531,0.002646176,0.0003516292,4.26e-7,0.01290811,0.000418259,0.0006108357],"study_design_scores_gemma":[0.0003535943,0.000005033213,0.9103085,0.0001349969,0.000006404955,2.894049e-7,0.0003924826,0.001461133,5.219087e-7,0.08367065,0.00352614,0.000140295],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9770183,0.01874648,0.0001013071,0.002489215,0.0003813638,0.0002690322,0.0001284904,0.00001449028,0.0008513288],"genre_scores_gemma":[0.9943942,0.001174884,0.0000558477,0.004178838,0.00002941348,0.00003622485,0.00002235094,0.000007090952,0.0001011937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07262277,"threshold_uncertainty_score":0.827369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2147121589762747,"score_gpt":0.408353179355811,"score_spread":0.1936410203795363,"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."}}