{"id":"W4380558739","doi":"10.32920/22227568","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":"McGill University Health Centre; McGill University","keywords":"Accountability; Legislation; Political science; Law; Public administration; Government (linguistics); State of emergency; Context (archaeology); Pandemic; Public health; Argument (complex analysis); Public health law; Public law; Politics; Health policy; Health care; Coronavirus disease 2019 (COVID-19); Medicine; International health","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":["research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009455265,0.0002083689,0.0004530371,0.00007503141,0.0001919697,0.000008207209,0.0003498145,0.0003969706,0.001748815],"category_scores_gemma":[0.005416055,0.0001410736,0.00003208647,0.0001957138,0.00008293669,0.00007417213,0.001084271,0.003482536,0.00004316593],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001158549,"about_ca_system_score_gemma":0.005682568,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9974288,"about_ca_topic_score_gemma":0.9997915,"domain_scores_codex":[0.9945612,0.002879062,0.00108276,0.0005483919,0.0003695475,0.0005590405],"domain_scores_gemma":[0.9923228,0.006504762,0.0001920022,0.0007787942,0.00006428092,0.0001373387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004740004,0.00002432113,0.9839725,0.000829676,0.000009877277,0.00001587874,0.0100707,0.00003521872,0.00001363675,0.0006295478,0.003715337,0.0002093287],"study_design_scores_gemma":[0.0002698242,0.000009333578,0.9180238,0.0004253456,0.00001020337,3.382505e-7,0.03918405,0.0003477876,0.000001237435,0.005993603,0.03555068,0.0001837797],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9332697,0.0002001848,0.000004653778,0.05975224,0.001581916,0.001198734,0.00002711463,0.00005993865,0.003905544],"genre_scores_gemma":[0.994929,0.0006979048,0.00002999818,0.002281331,0.0001243714,0.0003473843,0.000009439421,0.00002123572,0.001559316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06594867,"threshold_uncertainty_score":0.9999543,"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."}}