REporting Guidelines for aCupuncture‐Related AdverSe Event Case Reports (RECASE): Elaboration and Explanation
Bibliographic record
Abstract
Case reports represent the earliest form of scientific literature to identify and describe adverse events (AEs) associated with medical interventions, and they still represent important educational resources for ensuring the safe practice of such interventions. Although case reports on AEs related to acupuncture continue to be published, detailed information about the acupuncture procedure is often insufficiently reported in these studies, which may introduce an overstatement or exaggeration of the harm of acupuncture. Consequently, these reports fall short of evaluating causality and achieving the educational purpose of preventing future AEs. To help address these limitations, we developed the "REporting guidelines for aCupuncture-related AdverSe Event case reports" (RECASE) based on the CARE (CAse REports) reporting guidelines for case reports using the expert Delphi methodology. This guideline contains essential items for case reports on acupuncture-related AEs. We anticipate that this reporting guideline will encourage greater transparency, fairness, and comprehensiveness in future case reports on acupuncture-related AEs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".