Acupuncture-Related Techniques: What To Do When Acupuncture Is Not Enough
Bibliographic record
Abstract
Acupuncture has been widely accepted as valuable treatment for many pain and sport injuries in the United States and abroad. Medical literature reports varying rates of success for acupuncture treatment that is often as good or better than recovery seen with conventional biomedical therapeutics. However, all acupuncturists recognize that not all of their patients' pain and sport injuries are resolved through acupuncture. Acupuncture-related techniques may often eliminate pain and restore health and function when acupuncture alone has not succeeded. Techniques that have been generally recognized include moxibustion, cupping, scraping (Gwa Sha), various acupuncture microsystems (auricular, hand, scalp, etc.) and neural therapy. In addition, the current author proposes that prolotherapy is an invaluable acupuncture-related technique that leads to tissue regeneration and functional restoration, and should often be considered as a viable therapeutic modality when acupuncture has failed. The physiologic basis of joint and tissue regeneration through prolotherapy is presented along with a review of literature to provide an integrative understanding of the nature of tissue injury and repair mechanisms and therapeutic options when acupuncture fails to resolve a patient's condition. Prolotherapy is an invaluable acupuncture-related technique that has sound historical and physiologic bases, and produces enhanced clinical outcomes for many patients who have not experienced healing or recovery through acupuncture.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".