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Bibliographic record
Abstract
Objective: To investigate the efficacy of commonly available analgesics in the management of delayed-onset muscle soreness (DOMS) over an 8-day period, and to compare the efficacy between aspirin and acetaminophen. \n \nMethod: Forty-two subjects were recruited. DOMS was induced by using the isokinetic dynamometer (KinCom璲�) in standardized fashion in the nondominant knee extensor with subjects seated at 30 degree-angle velocity. Subjects were asked to extend their non-dominant knee with concentric method and to hold the knee with eccentric flexion force at 30 degree-angle velocity, with maximal efforts. On this way, they did 10 repetitions, and then 3 cycles. We categorized four groups (n=10, for each group), that were control group with no medication, placebo group with placebo medication (antacid tablets), aspirin group with medication of 900 mg of aspirin, and acetaminophen group with medication with 3,900 mg of acetaminophen. Visual Analogue Scale (VAS: twice a day, until on day 8). and McGill Pain Questionnaire (MPQ: on day 1 and 3) were measured. \n \nResults: We didn't find any significant difference of peak VAS score and relief time between four groups (P竊�0.05), The score of MPQ was not different between four groups (P竊�0.05). \n \nConclusion: We concluded that the medication may not be beneficial, at least at the doses stated, in the management of DOMS.
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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) | 0.002 | 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 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".