{"id":"W2969904913","doi":"10.5430/jnep.v9n12p27","title":"Bedside clinicians retain nurses through turnover analysis and best practices","year":2019,"lang":"en","type":"article","venue":"Journal of Nursing Education and Practice","topic":"Geriatric Care and Nursing Homes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Credentialing; Economic shortage; Turnover; Metropolitan area; Nursing; Nursing shortage; Business; Corporate governance; Medicine; Health care; Best practice; Quality (philosophy); Government (linguistics); Political science; Finance; Management; Nurse education","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":[0.01907898,0.0003674827,0.0003846822,0.003594561,0.002315089,0.007412968,0.001296503,0.0007642396,0.00173846],"category_scores_gemma":[0.04657619,0.0003228798,0.0006094885,0.002571973,0.0007504484,0.004242681,0.00227748,0.001433089,0.0004504598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005284912,"about_ca_system_score_gemma":0.01297055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01018914,"about_ca_topic_score_gemma":0.03800819,"domain_scores_codex":[0.9858392,0.005546559,0.001150027,0.0009284717,0.005702666,0.0008329825],"domain_scores_gemma":[0.9710286,0.008759853,0.006621289,0.00149368,0.009951503,0.002145109],"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":[0.0001468569,0.00136102,0.3391573,0.0003615342,0.0001545619,0.0001290049,0.01231455,0.001967866,0.0004863457,0.003736679,0.0182746,0.6219096],"study_design_scores_gemma":[0.0002539179,0.002464181,0.6708607,0.005594094,0.000673748,0.001047872,0.135236,0.05362707,0.006779014,0.02406156,0.09896941,0.0004324309],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8766202,0.002813662,0.04096974,0.02883263,0.0003682892,0.001079193,0.0008427426,0.0007243117,0.04774928],"genre_scores_gemma":[0.9434068,0.00124318,0.04890643,0.001114507,0.000124247,0.0003595823,0.0004747981,0.00007078084,0.004299649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01907898,"threshold_uncertainty_score":0.1009005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1779208579069698,"score_gpt":0.565369603502935,"score_spread":0.3874487455959652,"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."}}