{"id":"W2404334088","doi":"","title":"Integration of electronic health records into nursing education: issues, challenges and limitations.","year":2015,"lang":"en","type":"article","venue":"PubMed","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Health records; Context (archaeology); Electronic health record; Computer science; Health informatics; Nurse education; Nursing; Data science; Medical education; Medicine; Health care; Public health; Political science","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":[0.1444569,0.000657784,0.0008232991,0.005250915,0.004032547,0.01178475,0.005516743,0.002987745,0.003256756],"category_scores_gemma":[0.2393814,0.0009898084,0.001003947,0.007686618,0.003756054,0.01721904,0.01348188,0.004218978,0.00125907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005501549,"about_ca_system_score_gemma":0.01543629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007122086,"about_ca_topic_score_gemma":0.01216135,"domain_scores_codex":[0.7969106,0.1388096,0.01771387,0.005015647,0.03810456,0.003445751],"domain_scores_gemma":[0.6607302,0.2313901,0.01562438,0.03362396,0.0517723,0.006859059],"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":[0.00009217834,0.0008618166,0.05018384,0.003764246,0.0001389456,0.0005016805,0.0234813,0.0006013833,0.001780299,0.008701939,0.004748939,0.9051434],"study_design_scores_gemma":[0.0001396949,0.002654475,0.1789896,0.0491959,0.0005898867,0.0102436,0.277254,0.01144138,0.01394681,0.03686165,0.4181905,0.0004924746],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3866402,0.04598334,0.2289553,0.2410585,0.00403665,0.005395878,0.0007847617,0.001500171,0.08564518],"genre_scores_gemma":[0.6314298,0.01243582,0.3390554,0.008053758,0.001030895,0.001894473,0.0006121057,0.0002459974,0.005241635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1444569,"threshold_uncertainty_score":0.7639701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2209499479860245,"score_gpt":0.4514225227834021,"score_spread":0.2304725747973776,"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."}}