{"id":"W4293660667","doi":"10.1016/j.ijregi.2022.08.011","title":"Excess deaths during the COVID-19 pandemic in Alberta, Canada","year":2022,"lang":"en","type":"article","venue":"IJID Regions","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Alberta; Alberta Health; Alberta Health Services","funders":"","keywords":"Excess mortality; Pandemic; Medicine; Coronavirus disease 2019 (COVID-19); Demography; Mortality rate; Disease; Infectious disease (medical specialty); Surgery; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006201625,0.0004030604,0.0002319784,0.001166229,0.001156319,0.0009614465,0.0007769321,0.000369625,0.001964367],"category_scores_gemma":[0.001204606,0.0001989366,0.0005309749,0.001802875,0.0004132748,0.0003146011,0.0007396068,0.0005727744,0.0001475654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0260796,"about_ca_system_score_gemma":0.02841213,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9939752,"about_ca_topic_score_gemma":0.9965219,"domain_scores_codex":[0.9995371,0.0000356012,0.00001936856,0.00004745403,0.0001737398,0.0001867472],"domain_scores_gemma":[0.9992149,0.00003928026,0.0001443773,0.00001628091,0.0003632782,0.0002219122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002767078,0.00003191221,0.9654381,0.0001640838,0.0001402094,0.0003840805,0.0004154059,0.004057452,0.000365062,0.0004690185,0.008961544,0.01929638],"study_design_scores_gemma":[0.00001980605,0.00003075934,0.9930594,0.000105976,0.00004951576,0.000110297,0.000916718,0.002614501,0.00008595383,0.000121655,0.002865989,0.0000193304],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9645193,0.004471993,0.0005660204,0.002842992,0.0001202426,0.00007315287,0.01752485,0.0001007994,0.00978065],"genre_scores_gemma":[0.9904612,0.001876632,0.0003929714,0.0003849032,0.00003112757,0.00001541532,0.004932415,0.000008602021,0.001896702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0260796,"threshold_uncertainty_score":0.1892216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07583071436983987,"score_gpt":0.364882659319538,"score_spread":0.2890519449496981,"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."}}