Bibliographic record
Abstract
Volume XV, Number 3, May 2014 West Open Access at www.westjem.com ISSN 1936-900X Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health TECHNOLOGY IN EMERGENCY CARE USEFUL: Ultrasound Exam for Underlying Lesions: Incorporation into Standard Physical Exam: J Steller, B Russell, S Lotfipour, G Maldonado, T Siepel, H Jakle, S Hata, A Chiem, JC Fox EMERGENCY DEPARTMENT OPERATIONS Does Prolonged Length of Stay in the Emergency Department Affect Outcome for Stroke Patients? M Jain, D Damania, AR Jain, AR Kanthala, LG Stead, BS Jahromi Follow Up for Emergency Department Patients After Intravenous Contrast and Risk of Nephropathy Skin Infections and Antibiotic Stewardship: Analysis of Emergency Department Prescribing Practices, 2007-2010 GW Hassen, A Hwang, LL Liu, F Mualim, T Sembo, TJ Tu, DH Wei, P Johnston, A Costea, C Meletiche, S Usmani, A Barber, R Jaiswal, H Kalantari DJ Pallin, CA Camargo, JD Schuur EDUCATION Survey of Publications and the H-index of Academic Emergency Medicine Professors M Babineau, C Fischer, K Volz, LD Sanchez Study of Medical Students’ Malpractice Fear and Defensive Medicine: A “Hidden Curriculum?” Scholar Quest: A Residency Research Program Aligned with Faculty Goals Experience with Emergency Ultrasound Training by Canadian Emergency Medicine Residents WF Johnston, RM Rodriguez, D Suarez, J Fortman AR Panchal, KR Denninghoff, B Munger, SM Keim DJ Kim, J Theoret, MM Liao, JL Kendall ETHICAL AND LEGAL Assessment of the Acute Psychiatric Patients in the Emergency Department: Legal Cases and Caveats B Good, RM Walsh, G Alexander, G Moore Informed Consent Documentation for Lumbar Puncture in the Emergency Department PB Patel, HE Anderson, LD Keenly, DR Vinson Contents continued on page ii A Peer-Reviewed, International Professional Journal
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.855 | 0.786 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".