{"id":"W3034185073","doi":"10.1101/2020.06.14.20130815","title":"Assessing the burden of COVID-19 in Canada","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; Université de Montréal; Center for Interuniversity Research and Analysis on Organizations","funders":"European Commission; Public Health Agency; Public Health Agency of Canada; McGill University","keywords":"Demography; Case fatality rate; Medicine; Per capita; Coronavirus disease 2019 (COVID-19); Outbreak; Public health; Health care; Disease; Gerontology; Geography; Environmental health; Population; Economic growth; Nursing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001286582,0.000447283,0.0004475407,0.002039244,0.001502654,0.00167843,0.001092421,0.0003010767,0.002288676],"category_scores_gemma":[0.003323576,0.0002237434,0.000591345,0.004235232,0.0005320508,0.0004027481,0.001015034,0.0006375843,0.000168063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05253614,"about_ca_system_score_gemma":0.05702407,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9968906,"about_ca_topic_score_gemma":0.9970252,"domain_scores_codex":[0.9988933,0.0001181505,0.00005475884,0.000113538,0.0004490505,0.0003711565],"domain_scores_gemma":[0.9969205,0.0002113356,0.0004767707,0.00006624108,0.001656823,0.0006684149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001348102,0.00002921256,0.9624124,0.0003236583,0.0003577054,0.0001450631,0.0003739248,0.002244877,0.0002890971,0.0009916306,0.01172499,0.02097253],"study_design_scores_gemma":[0.00001881252,0.00003710102,0.9859331,0.0002502143,0.0001220535,0.00008165887,0.001028706,0.003273509,0.000213339,0.0002007003,0.008814539,0.00002615788],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8758669,0.01515925,0.002584153,0.007657338,0.0001188649,0.0002723283,0.08043338,0.0001730293,0.01773483],"genre_scores_gemma":[0.9791608,0.004227736,0.001716051,0.0005635174,0.000026067,0.00004116278,0.01239526,0.0000231387,0.001846291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05253614,"threshold_uncertainty_score":0.3811782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1536683550016155,"score_gpt":0.4346500025737516,"score_spread":0.2809816475721362,"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."}}