{"id":"W4293243736","doi":"10.23889/ijpds.v7i3.2064","title":"The Impact of the COVID-19 Pandemic on End-of-Life Prescribing in Ontario Nursing Homes.","year":2022,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Canadian Institute for Health Information; McMaster University; Alberta Health Services; University Health Network; Ottawa Hospital; Bruyère","funders":"","keywords":"Medicine; Pandemic; Medical prescription; Coronavirus disease 2019 (COVID-19); Nursing homes; Retrospective cohort study; Outbreak; Demography; Family medicine; Emergency medicine; Nursing; Disease; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0007895379,0.0002053348,0.0002050652,0.0007837206,0.0014435,0.001105672,0.0008022238,0.0003772964,0.002042254],"category_scores_gemma":[0.005163982,0.0002474708,0.0006404457,0.001424081,0.0004820826,0.0006149398,0.001155687,0.000507392,0.0001826299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02014067,"about_ca_system_score_gemma":0.01931668,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9535149,"about_ca_topic_score_gemma":0.9809867,"domain_scores_codex":[0.9985849,0.0001527238,0.000118164,0.0001911448,0.0004712809,0.0004817424],"domain_scores_gemma":[0.9958495,0.0002544368,0.001991972,0.0001217796,0.001007648,0.0007746269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003699812,0.00001773225,0.9950939,0.00003637412,0.00002635356,0.00004608739,0.0006681072,0.00004068013,0.00006445318,0.00004143965,0.000718912,0.003209068],"study_design_scores_gemma":[0.000002490612,0.00001263428,0.9987627,0.00002848534,0.0000079302,0.0000164432,0.0005389251,0.00007280663,0.00001705974,0.000009583243,0.0005275348,0.000003450675],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899126,0.001135285,0.0001245605,0.001439606,0.00002983514,0.00005392562,0.004347757,0.000009144036,0.002947373],"genre_scores_gemma":[0.9970376,0.00057824,0.000200042,0.0002762097,0.00001844661,0.00003477612,0.001002965,0.000004330615,0.0008473521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04648513,"threshold_uncertainty_score":0.1461315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2598634533794018,"score_gpt":0.5191243138093234,"score_spread":0.2592608604299217,"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."}}