{"id":"W2952874730","doi":"10.1002/nop2.321","title":"Nurse staffing models in acute care: A descriptive study","year":2019,"lang":"en","type":"article","venue":"Nursing Open","topic":"Nursing education and management","field":"Nursing","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Clinical Research Institute","funders":"","keywords":"Overtime; Staffing; Nursing; Agency (philosophy); Acute care; Descriptive statistics; Medicine; Health care; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002149084,0.00016003,0.0002018471,0.001581077,0.001158853,0.001036875,0.0005813165,0.0002416071,0.001046893],"category_scores_gemma":[0.004862601,0.0002285065,0.0002226746,0.001923106,0.0006348075,0.000804394,0.0006640985,0.000398267,0.0001518978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005139284,"about_ca_system_score_gemma":0.004164541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1176465,"about_ca_topic_score_gemma":0.1958989,"domain_scores_codex":[0.9990602,0.0002501764,0.0001155318,0.00007805793,0.0002866287,0.0002093554],"domain_scores_gemma":[0.9965171,0.0009164157,0.001182386,0.000116887,0.0009271191,0.0003401711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004459935,0.0001308566,0.9813707,0.00004298426,0.000008981525,0.0001333416,0.01160926,0.00007466322,0.0001689052,0.00008868134,0.0002804289,0.006046504],"study_design_scores_gemma":[0.000004381176,0.0002311286,0.9509105,0.00006215632,0.000007098523,0.0003511545,0.04674124,0.0003682311,0.0001091958,0.00004098772,0.001159935,0.0000139782],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990647,0.000108099,0.0001322523,0.00003619656,0.000001685982,0.00004115219,0.0001856319,0.000002509857,0.0004277486],"genre_scores_gemma":[0.9991178,0.0001392515,0.0002233415,0.00002436126,0.000002182042,0.00005569897,0.0002138049,0.000001562125,0.0002221608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1176465,"threshold_uncertainty_score":0.2339235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03986042862026175,"score_gpt":0.3551279413444476,"score_spread":0.3152675127241859,"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."}}