Bibliographic record
Abstract
Objectives : The Knee degenerative osteoarthritis patients are not satisfied with the conventional therapies of KDOA, which results in the use of alternative therapies. The miniscalpel acupuncture is effective in treating chronic soft tissue, releasing contractures. However, there is little scientific evidence supporting the use of miniscalpel acupuncture in knee degenerative osteoarthritis. This study was designed to obtain basic data for a further large-scale trial as well as provide information about the feasibility of miniscalpel acupuncture in knee degenerative osteoarthritis patients. Methods : We describe the protocol for a randomized controlled pilot clinical trial of 5 weeks duration. Twenty patients will be recruited and randomly allocated to two treatment groups: miniscalpel acupuncture treatment (experimental group); and acupuncture and electro-acupuncture treatment(control group). Miniscalpel acupuncture will be performed once with a 1-week interval for 3 weeks. Electro-acupuncture will be administered twice per week for a period of 3 weeks. The primary outcomes will be measured by visual analogue scale and range of motion. The secondary outcomes will be short-form McGill Pain Questionnaire and Western Ontario and McMaster Universities Osteoarthritis Index. Both primary and secondary outcomes will be measured at baseline and at 1, 2, 3 and 5 weeks(i.e. 2 weeks after treatment completion). Conclusions : This pilot study will provide a basic foundation for a future large-scale trial as well as information about the feasibility of miniscalpel acupuncture in knee degenerative osteoarthritis.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".