{"id":"W2822508593","doi":"10.5430/jha.v7n5p17","title":"Engaging patients through Multi-Disciplinary Rounding – The case study at a Michigan hospital","year":2018,"lang":"en","type":"article","venue":"Journal of Hospital Administration","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rounding; Patient satisfaction; Medicine; Process (computing); Nursing; Patient care; Health care; Medical education; Computer science; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006536607,0.0001769071,0.0002372856,0.0001240669,0.00083593,0.0002432833,0.000249405,0.00008417964,0.00001658848],"category_scores_gemma":[0.0001910742,0.0001202447,0.000101352,0.0002800782,0.00009960819,0.001380324,0.0001781864,0.0002997931,0.00004144193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008034072,"about_ca_system_score_gemma":0.00005429899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004261611,"about_ca_topic_score_gemma":0.001958412,"domain_scores_codex":[0.9985217,0.00003905896,0.0006891257,0.0002015774,0.0002923482,0.0002562121],"domain_scores_gemma":[0.9982044,0.00003929773,0.0009760558,0.0002147656,0.0005445957,0.00002089678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001144529,0.003903164,0.9735472,0.0001135785,0.0001603986,0.002773463,0.01123806,0.000001836878,0.00005232919,0.001790582,0.001774566,0.004530346],"study_design_scores_gemma":[0.0109663,0.04718195,0.5765853,0.0006072431,0.000637454,0.003438709,0.3297744,0.001900531,0.0004477998,0.003726855,0.02284865,0.001884794],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941092,0.00004265223,0.0002011492,0.001932659,0.002680469,0.0005574641,0.000001639703,0.00003958721,0.0004351906],"genre_scores_gemma":[0.9972743,0.000001571785,0.0002096923,0.0001393634,0.002294161,0.000009617433,0.000003957935,0.00002247603,0.00004480172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.396962,"threshold_uncertainty_score":0.6429382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03204309921611784,"score_gpt":0.3092076779964975,"score_spread":0.2771645787803796,"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."}}