{"id":"W4323322414","doi":"10.37964/cr24764","title":"PERSPECTIVE: Lessons in crisis decision-making learned from Canada’s COVID-19 health care response","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Physician Leadership","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; Perspective (graphical); Health care; 2019-20 coronavirus outbreak; Political science; Clinical decision making; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Public relations; Prism; Medicine; Psychology; Family medicine; Virology; Computer science; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001793975,0.0002350163,0.0005364117,0.001161667,0.0008425946,0.00004318417,0.0005679606,0.0001180094,0.0002558819],"category_scores_gemma":[0.002294914,0.0002423902,0.0001399139,0.001056618,0.00007382294,0.0002274741,0.00004607777,0.000997646,0.0001220402],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.009552184,"about_ca_system_score_gemma":0.05108585,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9062883,"about_ca_topic_score_gemma":0.9962282,"domain_scores_codex":[0.9952075,0.001993271,0.0007661123,0.0003562937,0.0004842023,0.001192646],"domain_scores_gemma":[0.9953722,0.002014525,0.0004973321,0.0004153047,0.0002451719,0.00145551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.001751082,0.00002476411,0.002581266,0.0001996903,0.0001196625,0.002244484,0.3310154,0.0009404167,0.0000189936,0.002751835,0.6439682,0.01438421],"study_design_scores_gemma":[0.0009785882,0.0001082328,0.02578239,0.0008396154,0.00002056668,0.000002071135,0.8226188,0.00001160342,0.000001503636,0.004002166,0.1454229,0.0002115272],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.400014,0.003173464,0.0005304856,0.5894105,0.002067171,0.0008466757,0.0004462374,0.00005750622,0.00345395],"genre_scores_gemma":[0.9414557,0.00001973984,0.00009068473,0.05742155,0.0003779552,0.00001378359,0.00001234789,0.00004924243,0.0005589707],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5414417,"threshold_uncertainty_score":0.99425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2362304791235012,"score_gpt":0.4654288759672821,"score_spread":0.2291983968437809,"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."}}