{"id":"W2752908109","doi":"10.1016/j.ecns.2017.07.007","title":"Optimizing Transition to Practice Through Orientation: A Quality Improvement Initiative","year":2017,"lang":"en","type":"article","venue":"Clinical Simulation in Nursing","topic":"Simulation-Based Education in Healthcare","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"London Health Sciences Centre","funders":"London Health Sciences Centre","keywords":"Summative assessment; Experiential learning; Orientation (vector space); Nursing; Quality (philosophy); Transition (genetics); Quality management; Nursing practice; Psychology; Nurse education; Medical education; Medicine; Pedagogy; Formative assessment; Engineering; Management system","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001635199,0.000165463,0.0003838589,0.0001230422,0.0004928473,0.0001076025,0.0001157071,0.000199502,0.0001004913],"category_scores_gemma":[0.004642335,0.0001796571,0.0001162625,0.0002477599,0.0001449662,0.0009216504,0.00001747126,0.0004010264,0.00004314547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006442953,"about_ca_system_score_gemma":0.0003085987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001770759,"about_ca_topic_score_gemma":0.000008785368,"domain_scores_codex":[0.9969773,0.0003599566,0.001392952,0.0005385702,0.0004520819,0.0002791466],"domain_scores_gemma":[0.9942378,0.00319118,0.0006696172,0.0007010119,0.0009678011,0.0002325578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.005195886,0.003677065,0.2387745,0.0002752114,0.00008938838,0.00002206961,0.09139823,0.449645,0.0001086641,0.003839338,0.0003068765,0.2066678],"study_design_scores_gemma":[0.00876261,0.001158849,0.8585783,0.001962676,0.0001616804,0.000004350574,0.01596049,0.1071232,0.0002543883,0.00399969,0.001578579,0.0004551739],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7923548,0.00004545757,0.1427657,0.05358683,0.00318848,0.002058065,0.00001216875,0.0001076646,0.005880855],"genre_scores_gemma":[0.9598221,0.00001024935,0.03184303,0.007380307,0.0007647129,0.00005720784,0.00007040914,0.00002524204,0.00002676287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6198038,"threshold_uncertainty_score":0.7326204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2341930974313932,"score_gpt":0.600744833822258,"score_spread":0.3665517363908648,"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."}}