Topical Analgesic Improved or Maintained Ballistic Hip Flexion Range of Motion with Treated and Untreated Legs.
Bibliographic record
Abstract
had a TopAnalg or a placebo gel applied to their hamstrings, rested for 20-min and then either performed static or dynamic stretching. Prior to gel application and after stretching, participants were tested for passive static, active and ballistic hip flexion ROM. Near significant greater ballistic hip flexion ROM for both legs (treated: p = 0.08; 3.6%; contralateral: p = 0.1; 1.6%) were observed with the TopAnalg. With dynamic stretching, ballistic hip flexion ROM of both limbs at post-test (p=0.01-0.007; 3.3-4.2%) and post-10 minutes (p = 0.06-0.01; 2.7-4.1%) decreased with the placebo, whereas there were no significant reductions with the TopAnalg. There was a near significant higher active hip flexion ROM (stretched leg: p = 0.05; 4.6%), and significantly higher ballistic hip flexion ROM (p = 0.04-0.05; 3.4-3.5%) with static versus dynamic stretching for both legs. In conclusion, TopAnalg can increase hip flexion ROM of the treated and contralateral limbs. Secondly, static stretching contributed to greater ballistic ROM in both the stretched and non-stretched contralateral limbs. Hence, TopAnalg may be used to enhance flexibility training with rehabilitation or highly trained athletes.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".