{"id":"W4398765567","doi":"10.1097/cin.0000000000001148","title":"Automated Dispensing Cabinets and Nursing Workarounds","year":2024,"lang":"en","type":"article","venue":"CIN Computers Informatics Nursing","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Workaround; Nursing; Medicine; Psychology; Computer science; Operating system","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":[0.004049483,0.0004226277,0.000300165,0.002143696,0.0007936145,0.003502982,0.0008835782,0.0007669134,0.02153862],"category_scores_gemma":[0.04583715,0.000402817,0.0006612902,0.002206625,0.0005142225,0.001830426,0.000874879,0.000845376,0.0009832029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002919917,"about_ca_system_score_gemma":0.003657293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02222636,"about_ca_topic_score_gemma":0.02429783,"domain_scores_codex":[0.9952654,0.002244201,0.0002689713,0.0004443605,0.001238048,0.0005391028],"domain_scores_gemma":[0.9372471,0.04424929,0.008647681,0.00103863,0.007083518,0.00173386],"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":[0.005801085,0.002052651,0.3591516,0.000867374,0.0004359979,0.0005200833,0.002075189,0.08125958,0.002026354,0.03684206,0.03273265,0.4762353],"study_design_scores_gemma":[0.0004619553,0.002571054,0.5481785,0.001011344,0.0004725361,0.0006623392,0.01083631,0.3485676,0.00297653,0.05595392,0.0280831,0.0002248026],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9321528,0.007859359,0.01560644,0.006210216,0.0007646199,0.0002272536,0.001843468,0.0003566664,0.03497924],"genre_scores_gemma":[0.9884846,0.001253935,0.004952136,0.0001137765,0.000117443,0.00003941966,0.0003880206,0.00005424439,0.004596399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02222636,"threshold_uncertainty_score":0.07205385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04388471983047907,"score_gpt":0.4247845562228554,"score_spread":0.3808998363923763,"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."}}