{"id":"W3132964825","doi":"10.1503/cmaj.1095922","title":"Canada’s long road to a vaccine injury compensation program","year":2021,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prime minister; Compensation (psychology); Coronavirus disease 2019 (COVID-19); Work (physics); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Scheme (mathematics); Occupational safety and health; Medicine; Medical emergency; Operations research; Business; Computer security; Political science; Aeronautics; Virology; Engineering; Computer science; Law; Psychology; Outbreak","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004839819,0.0006609392,0.0006084171,0.001435409,0.01462994,0.006991642,0.002013552,0.006327888,0.04290029],"category_scores_gemma":[0.01243235,0.0006487085,0.001110266,0.001184382,0.002831365,0.002418151,0.004099878,0.009011652,0.003943155],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07113124,"about_ca_system_score_gemma":0.5078741,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9822948,"about_ca_topic_score_gemma":0.9917569,"domain_scores_codex":[0.9914109,0.000593705,0.0001654305,0.0003853116,0.004039701,0.003404927],"domain_scores_gemma":[0.9680747,0.001226783,0.0003676081,0.0005078107,0.01149552,0.01832763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008480452,0.0001272517,0.00365633,0.0002009943,0.00003212046,0.000178177,0.0004702412,0.0001822492,0.000351832,0.03000244,0.9294267,0.03528691],"study_design_scores_gemma":[0.00009873994,0.00008252163,0.01418461,0.0002724361,0.00002323857,0.00005618804,0.0006204162,0.0002619907,0.0001377432,0.001684665,0.9825301,0.00004734784],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.008765193,0.005787259,0.001650661,0.8240272,0.009981342,0.0003701647,0.003797818,0.0004959444,0.1451243],"genre_scores_gemma":[0.1152818,0.009340484,0.01053694,0.405995,0.002188111,0.0004630736,0.005035827,0.0002746738,0.4508842],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9288688,"threshold_uncertainty_score":0.5160958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009502536086597294,"score_gpt":0.2737955700411872,"score_spread":0.2642930339545899,"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."}}