{"id":"W3197095260","doi":"10.2196/28998","title":"Measuring Collaboration Through Concurrent Electronic Health Record Usage: Network Analysis Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine; National Institutes of Health; National Science Foundation","keywords":"Audit; Metric (unit); Concurrent validity; Electronic health record; Computer science; Health care; Electronic medical record; Medicine; Medical emergency; Nursing; Operations management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007820435,0.000365449,0.0003230383,0.003969057,0.0008462793,0.001417706,0.0007535539,0.0006168493,0.001274205],"category_scores_gemma":[0.04004527,0.0002682408,0.0005241443,0.004031471,0.0005354423,0.002333093,0.001779538,0.0006873705,0.0002503648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001294701,"about_ca_system_score_gemma":0.001171378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006846251,"about_ca_topic_score_gemma":0.007180168,"domain_scores_codex":[0.9911341,0.005429035,0.0007031219,0.001074781,0.001125358,0.0005335641],"domain_scores_gemma":[0.9427158,0.03592949,0.01175434,0.002403504,0.004734241,0.002462623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001393309,0.0003634102,0.9795585,0.00006043839,0.0001933818,0.00006744294,0.002527901,0.001002924,0.0002796424,0.0003754211,0.000362563,0.01506899],"study_design_scores_gemma":[0.00003605683,0.0007008159,0.9486892,0.00009071189,0.0002030695,0.0004722497,0.01071995,0.03566611,0.0007121162,0.0009735406,0.001686397,0.00004971484],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938013,0.0001001624,0.00439342,0.0001419694,0.000008395323,0.0001207095,0.0003280196,0.00001271749,0.001093421],"genre_scores_gemma":[0.9960544,0.0000952278,0.003174967,0.00003655448,0.00001735249,0.0001397801,0.0003048219,0.00000593183,0.0001709741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007820435,"threshold_uncertainty_score":0.04135895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03602453678301801,"score_gpt":0.325436051692146,"score_spread":0.289411514909128,"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."}}