{"id":"W4398252103","doi":"10.1097/ncm.0000000000000740","title":"Developing and Deploying Emotional Intelligence to Uncover and Address Clients’ Needs","year":2024,"lang":"en","type":"article","venue":"Professional Case Management","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Capital Commission","funders":"","keywords":"Computer science; MEDLINE; Emotional intelligence; Psychology; Data science; Social psychology","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":[0.01049883,0.0006037868,0.0004426436,0.002088712,0.001476598,0.004959248,0.001858433,0.0008796788,0.007661748],"category_scores_gemma":[0.04465995,0.0003661863,0.0005939736,0.0009479468,0.0009553838,0.003264886,0.004530124,0.002613437,0.002149159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001646696,"about_ca_system_score_gemma":0.006392938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003795727,"about_ca_topic_score_gemma":0.00938478,"domain_scores_codex":[0.9954775,0.001938497,0.0003294159,0.0004256513,0.001325027,0.0005038821],"domain_scores_gemma":[0.9821506,0.009740789,0.001268493,0.001354902,0.003231042,0.002254136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001247167,0.001837505,0.05475148,0.0003816148,0.00005473988,0.0003036603,0.01278445,0.001000998,0.002188382,0.002625199,0.04018733,0.88376],"study_design_scores_gemma":[0.0008025233,0.002824117,0.243266,0.007275729,0.001035589,0.004304097,0.1460976,0.098391,0.03999018,0.1360503,0.319348,0.0006148939],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4216593,0.003795884,0.2753227,0.09825312,0.00167517,0.005200001,0.001077844,0.009236132,0.1837798],"genre_scores_gemma":[0.587443,0.002940736,0.3846852,0.005636338,0.0002503244,0.001873914,0.0009885306,0.0004356947,0.0157462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01049883,"threshold_uncertainty_score":0.05552381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1052044115563902,"score_gpt":0.4564226780439419,"score_spread":0.3512182664875517,"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."}}