{"id":"W3109322135","doi":"10.1093/jlb/lsaa083","title":"Transparency too little, too late? Why and how Health Canada should make clinical data and regulatory decision-making open to scrutiny in the face of COVID-19","year":2020,"lang":"en","type":"article","venue":"Journal of Law and the Biosciences","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Dalhousie University","funders":"Canadian Institutes of Health Research","keywords":"Scrutiny; Transparency (behavior); Coronavirus disease 2019 (COVID-19); Open data; Face (sociological concept); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Public relations; Business; Internet privacy; Political science; Medicine; Infectious disease (medical specialty); Computer science; Virology; Sociology; Disease; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.1048127,0.000516124,0.001198543,0.002919293,0.009207943,0.02530696,0.003566797,0.01900302,0.006031186],"category_scores_gemma":[0.2805584,0.000829392,0.001169612,0.003336665,0.03216888,0.02090557,0.004927785,0.02604772,0.001518838],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05979526,"about_ca_system_score_gemma":0.1804589,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4825793,"about_ca_topic_score_gemma":0.4268986,"domain_scores_codex":[0.9174383,0.03514663,0.002637513,0.005124394,0.02865536,0.01099779],"domain_scores_gemma":[0.687912,0.1488092,0.02283126,0.01469916,0.09016132,0.03558704],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000209118,0.0001001772,0.007682759,0.0004619804,0.0001682944,0.0003105736,0.003266534,0.001619085,0.000525982,0.5656032,0.3465366,0.07351579],"study_design_scores_gemma":[0.0002121385,0.00007420603,0.008115285,0.002163315,0.0001149423,0.0003062793,0.003265341,0.003580979,0.0009770216,0.6530842,0.3277564,0.0003499208],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001814717,0.003583863,0.002618453,0.9829276,0.001059986,0.00002773241,0.00009546577,0.00004303291,0.007829208],"genre_scores_gemma":[0.3317612,0.01194345,0.01097996,0.6291295,0.006615629,0.00009884567,0.0001588288,0.0002460828,0.009066538],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9964332,"threshold_uncertainty_score":0.9595407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3147006229163092,"score_gpt":0.4130119418054523,"score_spread":0.09831131888914302,"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."}}