{"id":"W4281844011","doi":"10.2337/db22-268-or","title":"268-OR: Impact of the COVID-Pandemic on Antihyperglycemic Prescription Patterns in Canada","year":2022,"lang":"en","type":"article","venue":"Diabetes","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medical prescription; Medicine; Pandemic; Family medicine; Type 2 diabetes; Pharmacy; Coronavirus disease 2019 (COVID-19); Diabetes mellitus; Health care; Basal insulin; Disease; Internal medicine; Pharmacology; Infectious disease (medical specialty); Endocrinology; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.0004452267,0.0002507532,0.000305795,0.0009622465,0.00240607,0.001441295,0.0007795317,0.0004761363,0.005872948],"category_scores_gemma":[0.00183671,0.0002096969,0.0007406764,0.002526624,0.0005020316,0.0004334472,0.0009736695,0.001051465,0.0004012446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03754227,"about_ca_system_score_gemma":0.07131675,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996693,"about_ca_topic_score_gemma":0.9976102,"domain_scores_codex":[0.9992378,0.00003408025,0.00004220206,0.00008656691,0.0002018119,0.0003976852],"domain_scores_gemma":[0.9977002,0.0001009389,0.0003697044,0.00004859138,0.0009581131,0.0008225093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002519902,0.00007064806,0.9575635,0.0002082248,0.00009048596,0.0002778422,0.0007906926,0.0003337011,0.0003147311,0.0003821996,0.01781843,0.02189753],"study_design_scores_gemma":[0.0000165845,0.00002765369,0.9924233,0.0001197791,0.00002814709,0.00008041043,0.001460238,0.0004616004,0.0001122397,0.00004847138,0.005201619,0.00001999204],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9080793,0.00347765,0.0002807144,0.009369006,0.000165979,0.0001638955,0.05872299,0.00007586026,0.01966466],"genre_scores_gemma":[0.9785587,0.001869454,0.0005396153,0.002341411,0.00004651453,0.0000532203,0.01119182,0.00002453272,0.005374684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03754227,"threshold_uncertainty_score":0.2723895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09079750183829711,"score_gpt":0.3653877144264486,"score_spread":0.2745902125881515,"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."}}