{"id":"W4404033081","doi":"10.1016/j.gaceta.2024.102424","title":"Unequal impact of COVID-19 on excess deaths, life expectancy, and premature mortality in Spanish regions (2020-2021)","year":2024,"lang":"en","type":"article","venue":"Gaceta Sanitaria","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Economic and Social Research Council; National Institute for Health and Care Research; Medical Research Council; Centers for Disease Control and Prevention Foundation; Cancer Research UK; British Heart Foundation; Wellcome Trust; Amgen","keywords":"Coronavirus disease 2019 (COVID-19); Life expectancy; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Pandemic; Excess mortality; Betacoronavirus; Demography; MEDLINE; Medicine; Virology; Mortality rate; Environmental health; Biology; Population; Outbreak; Internal medicine; Disease","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005586233,0.0002911592,0.0006672911,0.0002754416,0.00007876571,0.00005470897,0.0001198508,0.000278483,0.0004723007],"category_scores_gemma":[0.001939472,0.0002369141,0.0001915643,0.00060208,0.0001013439,0.0001448591,0.00006894663,0.0006384212,0.00002113518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004597166,"about_ca_system_score_gemma":0.003200935,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007771011,"about_ca_topic_score_gemma":0.003414948,"domain_scores_codex":[0.9979123,0.0001599542,0.0005191991,0.000547967,0.0004074623,0.0004531035],"domain_scores_gemma":[0.9978979,0.0004950874,0.0001007725,0.0005815936,0.00007225032,0.0008523694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002709782,0.001114261,0.8734053,0.009174163,0.001029126,0.003528349,0.02588971,0.0002349374,0.003512473,0.01624279,0.06047481,0.002684295],"study_design_scores_gemma":[0.002189938,0.001313873,0.9859806,0.001167457,0.0002530484,0.0001131059,0.001014801,0.0006048974,0.00008238375,0.003362203,0.003568578,0.0003490802],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821213,0.007085385,0.0001218032,0.008300226,0.0003310065,0.0007673496,0.0001828199,0.0001103327,0.0009798148],"genre_scores_gemma":[0.9972793,0.0006700797,0.0000820612,0.001299142,0.0003780673,0.00002463866,0.00006273852,0.00004011851,0.0001637839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1125753,"threshold_uncertainty_score":0.9988363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07390159939616621,"score_gpt":0.4208421301015079,"score_spread":0.3469405307053417,"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."}}