{"id":"W4394183109","doi":"10.6084/m9.figshare.14036549.v2","title":"Estimated Deaths, Intensive Care Admissions and Hospitalizations Averted in Canada during the COVID-19 Pandemic","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Disaster Response and Management","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medicine; Intensive care; Emergency medicine; Demography; Medical emergency; Virology; Intensive care medicine; Outbreak; Infectious disease (medical specialty); Internal medicine; Sociology","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":[0.0008664114,0.0008107936,0.0005871189,0.003503958,0.00168036,0.001458292,0.001073261,0.0004798737,0.004410911],"category_scores_gemma":[0.006139416,0.0004030174,0.001460245,0.006234112,0.0003248549,0.0005218748,0.0008138379,0.0009810855,0.0009968346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0341135,"about_ca_system_score_gemma":0.04380634,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958327,"about_ca_topic_score_gemma":0.9965121,"domain_scores_codex":[0.9991087,0.00005621889,0.00006633079,0.0001326355,0.0003505433,0.0002855679],"domain_scores_gemma":[0.9962836,0.0002797375,0.0003740653,0.0001477043,0.00259924,0.0003156215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006922808,0.00009500591,0.4359882,0.001264437,0.001378798,0.0002701724,0.0005310182,0.04356126,0.0004663291,0.005842226,0.4561409,0.05376937],"study_design_scores_gemma":[0.000228637,0.00009729378,0.7498176,0.001176232,0.0005228152,0.0003963672,0.001492115,0.0447831,0.00122783,0.001531633,0.1984975,0.0002287601],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0746302,0.002378885,0.001147568,0.001185806,0.00006875111,0.00009821027,0.9103016,0.0004398902,0.009749095],"genre_scores_gemma":[0.330665,0.004910863,0.005910847,0.0008424197,0.00006574585,0.0002254664,0.6495549,0.0001506971,0.007674021],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0341135,"threshold_uncertainty_score":0.2475119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1240330129238984,"score_gpt":0.4096616393170269,"score_spread":0.2856286263931285,"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."}}