[Improving acupuncture research: progress, guidance, and future directions].
Bibliographic record
Abstract
. Studies show that the quality of randomized controlled trial (RCT) of acupuncture is low, and multivariable Meta-regression analysis fails to confirm most factors commonly believed to influence the effect of acupuncture. The methodological challenges in design and conduct of RCT in acupuncture were analyzed, and a consensus on how to design high-quality acupuncture RCT was developed. The number of acupuncture systematic reviews was huge but the evidence was underused in clinical practice and health policy, and a large number of western clinical practice guidelines recommended acupuncture therapy, but the usefulness of recommendations needed to be improved. In view of the problems in clinical research on acupuncture mentioned in this collection, combined with the analysis of the purpose of clinical research on acupuncture, perspectives, study types, as well as the relationship between evidence and clinical decision-making, a five-stage study paradigm of clinical research on acupuncture is proposed.
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 | 0.085 | 0.176 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.015 | 0.014 |
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".