{"id":"W4407402127","doi":"10.2139/ssrn.5132606","title":"Impact of COVID-19 on Mortality and Healthcare Resource Utilization Across a Population of 306 Million in Australia, Canada, Denmark, England and Wales, Japan, and South Korea: An Interrupted Time-Series Analysis","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); New england; Interrupted Time Series Analysis; Geography; Population; Population health; 2019-20 coronavirus outbreak; Interrupted time series; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Demography; Medicine; Environmental health; Outbreak; Political science; Virology; Psychological intervention","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003047134,0.0003232022,0.0006528278,0.0007917933,0.0003188845,0.001057683,0.0008957995,0.000861886,0.001672236],"category_scores_gemma":[0.01040662,0.0002628767,0.001454765,0.002803825,0.0004338016,0.000755842,0.001517175,0.001963668,0.0002758989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002400713,"about_ca_system_score_gemma":0.002335651,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2753373,"about_ca_topic_score_gemma":0.1648392,"domain_scores_codex":[0.9979193,0.0005991849,0.0003122739,0.0003231507,0.0003449005,0.0005012197],"domain_scores_gemma":[0.9941196,0.001461705,0.002114059,0.0004459389,0.0009138144,0.0009448039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004794536,0.00007457737,0.9929149,0.00004759298,0.000497041,0.00008680581,0.0001788623,0.0017974,0.0000542037,0.0002107619,0.001346283,0.002312081],"study_design_scores_gemma":[0.00001190345,0.00008407187,0.9954084,0.00002238403,0.0001315196,0.00003962142,0.0003989945,0.003063327,0.00003660858,0.00006992279,0.0007191542,0.00001407605],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863268,0.0005593286,0.0002997449,0.000545155,0.00004512215,0.0000243837,0.01160457,0.00001377418,0.0005810519],"genre_scores_gemma":[0.9881837,0.0003014547,0.0002313369,0.0001185904,0.0000277602,0.00003675917,0.01036546,0.000007306333,0.0007276537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7246627,"threshold_uncertainty_score":0.5474694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08049909438416358,"score_gpt":0.428957838976961,"score_spread":0.3484587445927975,"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."}}