Bibliographic record
Abstract
This issue of Journal of Pediatric Surgical Nursing, 11:02, is on safety. The issue begins with articles on infection. Both pharmacist Nang and nurse practitioner Pasarón have articles exploring the diarrhea condition of Clostridium difficile (C. diff). This is a very serious problem in healthcare, and per the Joint Commission, the total annual C. diff-attributable cost in the United States is approximately $6.3 billion and the total annual C. diff-related inpatient hospital days is nearly 2.4 million. An article by Lomba, Abreu, Oliveira, Pereira, Backes, and Graveto explains how both hospital and clinic nurses must protect the transmission of bacteria via their uniforms or scrubs. Bayless, discussing COVID-19 infection, provides a review of children's resources on the disease and getting vaccinated. Three articles discuss issues related to items potentially unsafe for children. Garcia, Cochrum, Dutton, and Nguyen report on pressure injuries from antithrombolytic stockings and how to prevent them. Lao, Theodorou, and Kohler, in Name the Diagnosis, reveal the dangers of magnets in children's toys and a case in which a child swallows them. Darcy and Barbanel-Yuni educate us on how to safely dispose of narcotics used postoperatively for children and describe the distribution of prepared activated carbon bags. The issue continues with a discussion of pediatric emergency department trauma practice. Dorman, Ciurzynski, and Wakeman report how the use of simulation drills can contribute to safety in the actual trauma response. The issue ends with an extremely thoughtful article by award-winning Dr. Quinn Grundy, from Canada. Grundy's contribution to safety is to ask us to carefully consider how we are using product vendors in healthcare. She asks the pediatric surgical nurse to evaluate how we buy, use, and educate about new products and cautions on the reliance we have come to have on sales representatives. We hope this issue will help to keep you practicing safely. We want to hear from our readers. Please write to us about the articles you read here. Your thoughts matter! Thank you, Anita Catlin, Editor, and Editorial Board Members, Journal of Pediatric Surgical Nursing.
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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 | 0.004 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.018 | 0.013 |
| Insufficient payload (model declined to judge) | 0.400 | 0.266 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".