Revolutionary pain relief cream and two-minute exercise to cure and prevent lower back pain
Bibliographic record
Abstract
Revolutionary pain relief cream and two-minute exercise to cure and prevent lower back pain In an interview with Open Access Government, Dr Helene Bertrand looks to her own back pain journey and the ways she has found to heal herself. Dr. Bertrand suffered from lower back pain for 37 years following the birth of her first child, but despite trying everything, she couldn't get the pain to go away. In 2003, she started working on prolotherapy after using it to relieve her own pain. This is when she started helping patients, and her demand skyrocketed. After conducting a research project on rotator cuff tendinopathy, she realised it was twice as good as physiotherapy in improving pain and function in the shoulder. She then published this paper on rotator cuff tendinopathy “Dextrose Prolotherapy Versus Control Injections in Painful Rotator Cuff Tendinopathy”(1) and started getting referrals. It was then that Helene decided she was going to concentrate on treating pain. After trying 16 different base creams, in 2014, they came up with QR cream, a quick pain relief cream made using Mannitol. She also came up with a two-minute exercise that could relieve lower back pain instantly.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".