{"id":"W4388177066","doi":"10.1016/j.puhe.2023.09.016","title":"Hospitalization and hospital mortality rates during the first and second waves of the COVID-19 pandemic in Quebec: interrupted time series and decomposition analysis","year":2023,"lang":"en","type":"article","venue":"Public Health","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal General Hospital; McGill University; Université de Sherbrooke; Université de Montréal; McGill University Health Centre","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research","keywords":"Medicine; Confidence interval; Pandemic; Interrupted Time Series Analysis; Excess mortality; Coronavirus disease 2019 (COVID-19); Demography; Epidemiology; Cause of death; Mortality rate; Pediatrics; Internal medicine; Disease; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001067695,0.0001139339,0.0003310746,0.0002823943,0.0002622597,0.0000661921,0.00005509427,0.00006743945,0.00003040754],"category_scores_gemma":[0.0005571424,0.00007362998,0.00003770157,0.001010071,0.0001878432,0.0002421224,0.00009378696,0.0001396975,5.358858e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002878887,"about_ca_system_score_gemma":0.0005625565,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02114611,"about_ca_topic_score_gemma":0.1101708,"domain_scores_codex":[0.9987925,0.0001693227,0.0003676599,0.0002369707,0.000162717,0.0002708781],"domain_scores_gemma":[0.9990704,0.0002065676,0.0001722195,0.0002134925,0.00005716881,0.0002801304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002608738,0.00002542782,0.9893805,0.0008845563,0.00008113969,0.000001938257,0.008567572,0.000004937411,0.00003873166,0.00006786911,0.0001393391,0.0007819296],"study_design_scores_gemma":[0.0005711658,0.000139537,0.9960489,0.0000516971,0.00004025827,0.00001343397,0.001058841,0.0009999193,0.00001340481,0.00009387983,0.0009013956,0.00006762275],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8991927,0.0004299843,0.00002475244,0.09972449,0.00003213867,0.0004982097,0.0000407318,0.00004618092,0.00001080618],"genre_scores_gemma":[0.996035,0.000757607,0.00000738649,0.00295754,0.00002643627,0.00001715511,0.00006106691,0.000009044395,0.0001288064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09684226,"threshold_uncertainty_score":0.9853722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04998669507899523,"score_gpt":0.3861138613085575,"score_spread":0.3361271662295623,"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."}}