{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002384897,0.0001086406,0.0001927358,0.000105635,0.0005629347,0.000008412314,0.0001770196,0.00003674205,0.0002781194],"category_scores_gemma":[0.0005548256,0.00008259386,0.00005171724,0.0004106988,0.00004647714,0.00002812663,0.0001078415,0.000502191,0.000004217246],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002279856,"about_ca_system_score_gemma":0.005729112,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9644886,"about_ca_topic_score_gemma":0.9879504,"domain_scores_codex":[0.9987331,0.0001177505,0.0002158338,0.0002186266,0.0003367499,0.0003779263],"domain_scores_gemma":[0.9986182,0.0005106905,0.00006071493,0.0004028152,0.00002049638,0.0003870572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002518,0.000108175,0.9336922,0.0003277803,0.00004235678,0.001011811,0.00496096,0.001284466,0.0002162336,0.001366291,0.05610213,0.0006357818],"study_design_scores_gemma":[0.001311666,0.00005899023,0.2592632,0.00002542879,0.00002462985,0.0009314598,0.001345742,0.00006824551,0.00000997864,0.0002490435,0.7365851,0.0001265473],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8050992,0.0003929447,0.00002096432,0.1928809,0.0002458158,0.0004365768,0.00002033808,0.00003863119,0.0008645311],"genre_scores_gemma":[0.9602051,0.00009756456,0.000004499807,0.03395101,0.0001160648,0.0001079968,0.00001463713,0.00001697884,0.005486144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.680483,"threshold_uncertainty_score":0.9999075,"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."}}