{"id":"W4282553966","doi":"10.1503/cmaj.212070","title":"COVID-19 and the prevalence of drug shortages in Canada: a cross-sectional time-series analysis from April 2017 to April 2022","year":2022,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Pharmaceutical Economics and Policy","field":"Economics, Econometrics and Finance","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women's College Hospital; University of Calgary","funders":"","keywords":"Economic shortage; Pandemic; Medicine; Medical prescription; Coronavirus disease 2019 (COVID-19); Demography; Government (linguistics); Environmental health; Internal medicine; Infectious disease (medical specialty); Pharmacology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.003411993,0.000089318,0.0003613541,0.0003391441,0.0003789636,0.00008035114,0.0003928132,0.00006195131,0.02269877],"category_scores_gemma":[0.001957216,0.00009271361,0.0001058478,0.0004345226,0.00007054894,0.00009930179,0.00008203067,0.0005796795,0.00002074087],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004020165,"about_ca_system_score_gemma":0.005355282,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8718379,"about_ca_topic_score_gemma":0.9555176,"domain_scores_codex":[0.9983633,0.0001272025,0.0007470092,0.0002211673,0.0002321112,0.0003092113],"domain_scores_gemma":[0.9978408,0.0003906681,0.0004001132,0.0001208711,0.00004199063,0.00120559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002769268,0.00000773089,0.9671271,0.000007295853,0.0002087761,0.00001913072,0.0004297022,0.001306417,2.383825e-7,0.002947495,0.02780608,0.0001123177],"study_design_scores_gemma":[0.0007659997,0.000007989519,0.7657152,0.000001543963,0.00002178482,0.00001074458,0.0001138599,0.004403805,4.990079e-7,0.00389394,0.2249503,0.0001143502],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9155211,0.001736041,0.00003152068,0.0754913,0.0005379639,0.0001440227,0.004525341,0.000003048681,0.002009612],"genre_scores_gemma":[0.9706749,0.0005154939,0.0000192733,0.02726911,0.0002328507,0.00002336493,0.00001977567,0.000007580101,0.001237678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2014119,"threshold_uncertainty_score":0.9998032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02103351348107317,"score_gpt":0.2660224292272247,"score_spread":0.2449889157461515,"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."}}