{"id":"W4311701728","doi":"10.1007/s12062-022-09405-2","title":"Correction: A Tale of Two Countries: Changes to Canadian and U.S. Senior Population Projections due to the Pandemic—Implications for Health Care Planning in Canada and Other Western Countries","year":2022,"lang":"en","type":"article","venue":"Journal of Population Ageing","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Ministry of Health and Long Term Care","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Political science; Health care; Population; Economic growth; Gerontology; Medicine; Demography; Sociology; Economics","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":[0.005681954,0.002879961,0.001969821,0.004292168,0.004532565,0.005207866,0.004783151,0.009233562,0.05268262],"category_scores_gemma":[0.1542071,0.001144239,0.001837182,0.005185724,0.003282677,0.003468094,0.00275228,0.01501057,0.02350039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01222663,"about_ca_system_score_gemma":0.02494547,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4183697,"about_ca_topic_score_gemma":0.3540055,"domain_scores_codex":[0.9935708,0.0009705727,0.001080686,0.000861735,0.002851638,0.0006646067],"domain_scores_gemma":[0.9196765,0.01209767,0.002888428,0.003252962,0.05873138,0.003353052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000008152376,9.199263e-7,0.00005818858,0.00003720704,0.000005539396,0.0000534663,0.00002562456,0.00002380097,0.000005903172,0.0002620943,0.9984308,0.001088243],"study_design_scores_gemma":[0.00005489845,0.000007479639,0.001701672,0.0006987567,0.00004072188,0.0003275444,0.0003050346,0.0004180277,0.000160083,0.001479592,0.9947351,0.00007120815],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"empirical","genre_scores_codex":[0.0001764803,0.001210963,0.0004603129,0.1489196,0.842414,0.00003277716,0.004259867,0.0003070577,0.002219014],"genre_scores_gemma":[0.03744058,0.01235058,0.005727238,0.2369373,0.5323207,0.0004715903,0.006330452,0.002413708,0.1660078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5816303,"threshold_uncertainty_score":0.8318689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04957044056997418,"score_gpt":0.321060180537229,"score_spread":0.2714897399672548,"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."}}