{"id":"W2413023851","doi":"10.3233/978-1-61499-633-0-126","title":"Incorporating Pharmacy Dispensing Records into Medical Records: Usability Challenges","year":2016,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Usability; Pharmacy; Medical record; Computer science; World Wide Web; Medicine; Family medicine; Human–computer interaction; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.1553062,0.00102885,0.001596275,0.003366486,0.002132012,0.01625604,0.003846804,0.003279931,0.002796708],"category_scores_gemma":[0.4688808,0.001774317,0.00169766,0.003431666,0.002471909,0.01262368,0.003691123,0.002706195,0.001413199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002683251,"about_ca_system_score_gemma":0.006167717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005696125,"about_ca_topic_score_gemma":0.01093355,"domain_scores_codex":[0.7264715,0.2060239,0.02021172,0.005006969,0.04079122,0.001494752],"domain_scores_gemma":[0.2024861,0.6999772,0.01091269,0.02613432,0.05912766,0.001362117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001003176,0.001805577,0.04649204,0.01202663,0.00114904,0.0005504518,0.0509346,0.001413436,0.007807238,0.004934943,0.01711267,0.8547702],"study_design_scores_gemma":[0.001382997,0.008613868,0.1717657,0.0381503,0.006832444,0.007388881,0.1579601,0.04402279,0.0419894,0.04719809,0.4728981,0.001797332],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5980999,0.03678356,0.2424553,0.05986245,0.002583789,0.006454078,0.002162326,0.005440407,0.04615817],"genre_scores_gemma":[0.6492044,0.008693132,0.3216103,0.008357927,0.00134366,0.002060936,0.001372272,0.001754336,0.005603044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1553062,"threshold_uncertainty_score":0.8213477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.160011409434794,"score_gpt":0.5041435023011064,"score_spread":0.3441320928663124,"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."}}