{"id":"W4382600516","doi":"10.14745/ccdr.v49i06a03","title":"Quantifying the economic gains associated with COVID-19 vaccination in the Canadian population: A cost-benefit analysis","year":2023,"lang":"en","type":"article","venue":"Canada Communicable Disease Report","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Economics; Health Canada; University of Toronto; Public Health Agency of Canada","funders":"Public Health Agency; Public Health Agency of Canada","keywords":"Vaccination; Medicine; Cost–benefit analysis; Population; Counterfactual thinking; Pandemic; Economic impact analysis; Economic evaluation; Demography; Environmental health; Coronavirus disease 2019 (COVID-19); Disease; Virology; Economics; Infectious disease (medical specialty); Internal medicine; Psychology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.001892591,0.0001627902,0.0003360231,0.0004414871,0.0008483644,0.0001210568,0.0005266984,0.0000630362,0.0000431528],"category_scores_gemma":[0.001406418,0.0001091066,0.0001205708,0.002213446,0.00005060924,0.00008117243,0.00007939932,0.0003831123,0.000005421491],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.006311459,"about_ca_system_score_gemma":0.01775867,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9949129,"about_ca_topic_score_gemma":0.9999106,"domain_scores_codex":[0.9978758,0.0002694985,0.0004227844,0.0002917688,0.0006452945,0.0004948918],"domain_scores_gemma":[0.9970537,0.0006829072,0.0001799479,0.00164381,0.0001428377,0.0002967979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006537057,0.00002364379,0.9883054,0.00002715013,0.0003813585,0.003527171,0.0001800417,0.003640647,0.0000015074,0.0003007011,0.003319067,0.0002278756],"study_design_scores_gemma":[0.0005552254,0.00001288988,0.9164447,0.000027985,0.0003941108,0.00004186542,0.0008777381,0.02550511,0.00000289962,0.00007344948,0.05592394,0.000140076],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808605,0.0003564688,0.000005740309,0.01469649,0.00004843315,0.0009818171,0.00009519293,0.00005721843,0.002898172],"genre_scores_gemma":[0.9648172,0.00001045552,0.000002655405,0.0339932,0.00002373243,0.0002256648,0.0008092367,0.00002160606,0.00009630091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07186075,"threshold_uncertainty_score":0.9975032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1168461488952936,"score_gpt":0.3870320932846964,"score_spread":0.2701859443894028,"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."}}