Bibliographic record
Abstract
BACKGROUND: Belief in efficacy of CAM therapies has been sparsely reported and may be different than reported use of the therapy. PURPOSE: The aim of this study was to identify efficacy beliefs of massage for muscle recovery following a 10-km running race. SETTING: Finish zone of a 10-km race. RESEARCH DESIGN: Participants completed a brief survey regarding running race characteristics, prior use of massage, and belief in efficacy of massage regarding muscle recovery from the race. PARTICIPANTS: The subject pool consisted of 745 individuals who completed a running race and were within 60 minutes of race completion. MAIN OUTCOME MEASURES: Subjects reported demographic information (age, gender), race information (finish time, perceived exertion, muscle soreness, fatigue), prior use of massage, and belief regarding efficacy of massage for postrace muscle recovery. RESULTS: Most study participants believed that massage would benefit muscle recovery following the running race (80.0%), even though only 43.9% had received a massage previously. Those who had received at least one massage were significantly more likely to believe that massage would benefit muscle recovery (91.9% vs. 70.4%, p < .001). Females were more likely than males to have had a massage (52.3% vs. 36.0%, p < .001) and to believe it would benefit recovery (83.1% vs. 77.1%, p = .046). CONCLUSIONS: Massage is well-accepted as a muscle recovery aid following a running race, but females and those who have used massage were significantly more likely to perceive it as advantageous. Belief in a therapeutic value of massage for muscle recovery exceeds its reported use.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".