{"id":"W4324046176","doi":"10.32920/22227568.v2","title":"Answering in Emergency: The Law and Accountability in Canada’s Pandemic Response","year":2023,"lang":"en","type":"preprint","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":"","keywords":"Accountability; Legislation; Political science; Public administration; Law; Government (linguistics); State of emergency; Context (archaeology); Argument (complex analysis); Public health law; Pandemic; Public health; Public law; Business; Politics; Health policy; Health care; Medicine; Coronavirus disease 2019 (COVID-19); Health care reform","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00574823,0.0003291966,0.0003348071,0.001863961,0.0367576,0.01562431,0.00196797,0.006885914,0.0121201],"category_scores_gemma":[0.02265089,0.0005456346,0.0004577959,0.002681729,0.01834261,0.004639837,0.0040489,0.008054536,0.000611636],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.245069,"about_ca_system_score_gemma":0.3681528,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9966905,"about_ca_topic_score_gemma":0.9978489,"domain_scores_codex":[0.9906436,0.00130575,0.0001860096,0.0006352842,0.003132401,0.00409694],"domain_scores_gemma":[0.9863948,0.004623308,0.0005943016,0.000384656,0.004424348,0.003578604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000510493,0.00004662458,0.009874483,0.0001159421,0.00002145542,0.00105521,0.0201511,0.001299312,0.0003094164,0.756802,0.1724994,0.03777405],"study_design_scores_gemma":[0.00005481016,0.00002825217,0.03327765,0.0004801499,0.00005451032,0.0003459715,0.04324149,0.004283697,0.0007201002,0.09641066,0.8208771,0.0002256451],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06315451,0.005815267,0.003188989,0.5725004,0.001430901,0.0001274967,0.0004722819,0.0001057108,0.3532044],"genre_scores_gemma":[0.8308434,0.004332076,0.002829125,0.05146131,0.0005532799,0.00005041405,0.0001872643,0.0001154149,0.1096277],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.754931,"threshold_uncertainty_score":0.875613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1463563794358048,"score_gpt":0.460750177417607,"score_spread":0.3143937979818023,"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."}}