{"id":"W3207722567","doi":"10.32920/22227568.v1","title":"Answering in Emergency: The Law and Accountability in Canada’s Pandemic Response","year":2023,"lang":"en","type":"article","venue":"","topic":"Medical Malpractice and Liability Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; McGill University; Université de Sherbrooke","funders":"McGill University Health Centre; McGill University","keywords":"Accountability; Political science; Legislation; Law; Public administration; State of emergency; Government (linguistics); Public law; Context (archaeology); Public health law; Public health; Pandemic; Criminal law; Politics; Health policy; Health care; Medicine; Coronavirus disease 2019 (COVID-19); Health care reform","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005425858,0.00007264978,0.0001538875,0.00004173035,0.0001722809,0.00000273901,0.000118038,0.00007772159,0.001697958],"category_scores_gemma":[0.002771682,0.00004633118,0.0000101132,0.00036156,0.0000449714,0.0001030815,0.0001205941,0.0006324354,0.00005993596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003214233,"about_ca_system_score_gemma":0.001279365,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9848063,"about_ca_topic_score_gemma":0.9991538,"domain_scores_codex":[0.9975755,0.00119717,0.0004563332,0.0001952031,0.0001940186,0.0003817645],"domain_scores_gemma":[0.9956775,0.003903059,0.0000460402,0.0002666231,0.00002512072,0.00008163802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002353647,0.000009883442,0.988089,0.00008282666,0.000001767131,0.000007159069,0.006725222,0.000003964976,0.00008491273,0.0009404696,0.003503756,0.0003157278],"study_design_scores_gemma":[0.0002278711,0.000008444522,0.8853375,0.00003998778,0.000001782,2.518007e-7,0.04697683,0.0002631848,0.000002896472,0.0009865389,0.06609763,0.00005707721],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9469187,0.00005178226,8.890059e-7,0.0462639,0.0003181192,0.0003831187,0.000003650329,0.00003795556,0.006021885],"genre_scores_gemma":[0.9962327,0.0001704584,0.000007534129,0.002483348,0.00004004048,0.00007447693,0.000001583885,0.000005905872,0.0009839804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1027514,"threshold_uncertainty_score":0.9992146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09162395093564701,"score_gpt":0.4429527656265239,"score_spread":0.3513288146908768,"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."}}