Executive Summary
Bibliographic record
Abstract
Enhanced Recovery After Surgery (ERAS) is a multimodal program developed to decrease postoperative complications, improve patient safety and satisfaction, and promote early discharge. In the province of Ontario, Canada, a standardized approach to the care of adult patients undergoing elective colorectal surgery (including benign and malignant diseases) was adopted by 15 hospitals in March 2013. All colorectal surgery patients with or without an ostomy were included in the ERAS program targeting a length of stay of 3 days for colon surgery and 4 days for rectal surgery. To ensure the individual needs of patients requiring an ostomy in an ERAS program were being met, a Provincial ERAS Enterostomal Therapy Nurse Network was established. Our goal was to develop and implement an evidence-based, ostomy-specific best practice guideline addressing the preoperative, postoperative, and discharge phases of care. The guideline was developed over a 3-year period. It is based on existing literature, guidelines, and expert opinion. This article serves as an executive summary for this clinical resource; the full guideline is available as Supplemental Digital Content 1 (available at: http://links.lww.com/JWOCN/A36) to this executive summary.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.392 | 0.288 |
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".