{"id":"W3087994124","doi":"10.1177/2327857920091056","title":"Cost vs. Benefit: What does NVivo Video Analysis of EMR Simulations Add to Our Understanding of User Experience?","year":2020,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Children's Hospital of Eastern Ontario; Carleton University","funders":"","keywords":"Workflow; Computer science; Context (archaeology); Coding (social sciences); Data collection; Data science; Sample (material); Knowledge management; Software; Database","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":[0.0004637305,0.0001532546,0.0004677766,0.0004088174,0.0003778687,0.00003470808,0.0005286124,0.00007797442,0.00007934068],"category_scores_gemma":[0.0004012727,0.0001137983,0.00009737557,0.0006748472,0.00006329886,0.0003826827,0.0002571012,0.0002291343,7.268882e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009432235,"about_ca_system_score_gemma":0.0001776579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001267813,"about_ca_topic_score_gemma":0.002540195,"domain_scores_codex":[0.9975073,0.00003774089,0.001363873,0.0003390336,0.0004348996,0.0003171792],"domain_scores_gemma":[0.9976904,0.000448682,0.001079686,0.000120263,0.0004227367,0.0002382656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001855822,0.00002430208,0.7668754,0.0005081712,0.00007038214,2.865943e-8,0.2118916,0.002806211,0.001947832,0.01528627,0.0003655303,0.00003873204],"study_design_scores_gemma":[0.001240735,0.0004327826,0.4856141,0.001309646,0.0000723475,1.133869e-7,0.4993015,0.002183504,0.004845999,0.0003792057,0.004299993,0.0003201022],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809705,0.00001076423,0.00002507331,0.01717591,0.0004224785,0.0008070761,0.0004497003,0.00001025567,0.000128261],"genre_scores_gemma":[0.9941508,0.0000760296,0.0001157388,0.005492632,0.00007076006,0.0000407629,0.00001521255,0.00001366748,0.000024464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2874099,"threshold_uncertainty_score":0.4640558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3466703740822136,"score_gpt":0.5304803187836644,"score_spread":0.1838099447014508,"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."}}