{"id":"W2028828949","doi":"10.1016/j.ijnurstu.2015.02.015","title":"Medical language proficiency: A discussion of interprofessional language competencies and potential for patient risk","year":2015,"lang":"en","type":"article","venue":"International Journal of Nursing Studies","topic":"Interpreting and Communication in Healthcare","field":"Health Professions","cited_by":94,"is_retracted":false,"has_abstract":false,"ca_institutions":"College of the Rockies; Thompson Rivers University","funders":"","keywords":"Health care; Jargon; CLARITY; Language barrier; Workforce; Psychology; Anticipation (artificial intelligence); Patient safety; Medical education; Medicine; Linguistics; Computer 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":[0.008825817,0.0002773014,0.0003485636,0.001886022,0.003374235,0.004998472,0.001420988,0.00228079,0.005724514],"category_scores_gemma":[0.04089805,0.0002392836,0.0007413836,0.00109592,0.003919786,0.005728408,0.006180984,0.003542128,0.0002760842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002684655,"about_ca_system_score_gemma":0.009174276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004316233,"about_ca_topic_score_gemma":0.008378952,"domain_scores_codex":[0.99523,0.002354838,0.0003667749,0.0003247579,0.001045423,0.0006783257],"domain_scores_gemma":[0.9722528,0.01978272,0.002461888,0.0003037576,0.002767414,0.002431444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003580353,0.000700519,0.3861201,0.0009286673,0.0001039488,0.009872608,0.1393341,0.0006775329,0.001670962,0.1256165,0.01327161,0.3213453],"study_design_scores_gemma":[0.00005071822,0.0007493304,0.2682286,0.004705227,0.0001948981,0.02239881,0.5526643,0.002485528,0.002284591,0.07603238,0.06999757,0.0002079828],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6852889,0.007814907,0.005391237,0.2538468,0.0005301135,0.00008919135,0.0001365039,0.0000214231,0.04688097],"genre_scores_gemma":[0.9906826,0.00240518,0.001350051,0.003677474,0.0002050065,0.00003943568,0.0000252366,0.000008077001,0.001607018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008825817,"threshold_uncertainty_score":0.04667598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06913329148751528,"score_gpt":0.5043586535918988,"score_spread":0.4352253621043835,"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."}}