{"id":"W1977765099","doi":"10.1006/jbin.2001.1028","title":"Patient Safety, Potential Adverse Drug Events, and Medical Device Design: A Human Factors Engineering Approach","year":2001,"lang":"en","type":"article","venue":"Journal of Biomedical Informatics","topic":"Patient Safety and Medication Errors","field":"Health Professions","cited_by":139,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Interface (matter); Patient safety; Context (archaeology); Computer science; Human error; Adverse effect; Medicine; Process (computing); Drug; Risk analysis (engineering); Medical emergency; Pharmacology; Health care","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001950297,0.0001899654,0.000418015,0.0003390794,0.0003803564,0.000002172786,0.0002763525,0.0003169596,0.0003030544],"category_scores_gemma":[0.001016231,0.0001350861,0.000107785,0.0003157748,0.0001280163,0.0003219135,0.0001551301,0.001178374,0.00002040737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000159848,"about_ca_system_score_gemma":0.0004664904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001108222,"about_ca_topic_score_gemma":0.000002025901,"domain_scores_codex":[0.9957892,0.000223238,0.002143929,0.00007859573,0.001322792,0.0004423043],"domain_scores_gemma":[0.9970374,0.0003815961,0.00121758,0.0001532079,0.0002035457,0.001006674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003409021,0.008810177,0.1363297,0.01129456,0.003549351,0.0009449002,0.5677841,0.01716447,0.001020455,0.004034386,0.1150658,0.130593],"study_design_scores_gemma":[0.0171729,0.002023217,0.08833515,0.00552134,0.0005699644,0.001254587,0.08831472,0.1129221,0.00006426842,0.0004104736,0.6820151,0.00139618],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5888675,0.00009403569,0.4073015,0.001592671,0.001151881,0.0004519159,0.00001039953,0.00003980513,0.0004903334],"genre_scores_gemma":[0.9853637,0.0003492063,0.01269824,0.001031558,0.00037611,0.00001032513,0.00005817088,0.00002046192,0.00009228127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5669494,"threshold_uncertainty_score":0.5508651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04332785147089331,"score_gpt":0.3466461989249985,"score_spread":0.3033183474541052,"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."}}