{"id":"W2409419932","doi":"10.7748/en.22.3.15.s16","title":"Making sure staff measure up","year":2014,"lang":"en","type":"article","venue":"Emergency Nurse","topic":"Healthcare Systems and Challenges","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Canadian Navy","funders":"","keywords":"Measure (data warehouse); Psychology; Nursing; Computer science; Medicine; Data mining","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":[0.04923171,0.001227524,0.001240792,0.001839691,0.01404651,0.01398901,0.003926015,0.02153393,0.01040825],"category_scores_gemma":[0.2034639,0.001248678,0.001591853,0.0008054759,0.01116862,0.01768109,0.01238427,0.04416658,0.009415965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008452977,"about_ca_system_score_gemma":0.04537784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01316773,"about_ca_topic_score_gemma":0.01572137,"domain_scores_codex":[0.9350358,0.02245927,0.004571745,0.005633737,0.02281221,0.009487302],"domain_scores_gemma":[0.8321636,0.04461165,0.008596652,0.009553157,0.05956546,0.04550957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004665862,0.0001358264,0.002366386,0.0001898639,0.0000648538,0.0002265106,0.006265397,0.0001420643,0.0006518555,0.02344942,0.89936,0.0671012],"study_design_scores_gemma":[0.00004908526,0.0001780766,0.003828878,0.0008828698,0.00004841814,0.0003792653,0.01289978,0.0003643443,0.001149015,0.03394489,0.9460378,0.0002375027],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.002066591,0.00174144,0.008163307,0.9244173,0.04641325,0.00006731694,0.00002333613,0.0003258357,0.01678155],"genre_scores_gemma":[0.0783046,0.001977554,0.0157242,0.8250519,0.009852588,0.0003264108,0.00008542687,0.000537335,0.06814007],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04923171,"threshold_uncertainty_score":0.2603652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1737599837575402,"score_gpt":0.4824986956014875,"score_spread":0.3087387118439473,"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."}}