Process for Developing Evidence-Informed Practice Recommendations
Bibliographic record
Abstract
In Brief PURPOSE To provide the wound care practitioner with an overview of the search process for venous leg ulcer clinical practice guidelines and appraisal of their quality applying the Appraisal of Guideline Research and Evaluation (AGREE) Instrument. TARGET AUDIENCE This continuing education activity is intended for physicians and nurses with an interest in skin and wound care. OBJECTIVES After reading this article and taking this test, the reader should be able to: Describe the process used to identify and review current wound care guidelines. Describe how the AGREE Instrument evaluates the methodological quality of practice guidelines. In this continuing education activity, the authors describe the search process for venous leg ulcer clinical practice guidelines, appraisal of their quality applying the Appraisal of Guideline Research and Evaluation (AGREE) Instrument, and discuss the importance of comparing recommendations.
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 | 0.340 | 0.522 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.021 | 0.014 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.012 | 0.024 |
| Research integrity | 0.023 | 0.032 |
| Insufficient payload (model declined to judge) | 0.037 | 0.027 |
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".