Effect of Pseudoephedrine on 800-m-Run Times of Female Collegiate Track Athletes
Bibliographic record
Abstract
CONTEXT: Pseudoephedrine (PSE) is an over-the-counter decongestant that might have ergogenic effects. The World Anti-Doping Agency has prohibited large doses (>150 μg/mL) of PSE, while the National College Athletic Association (NCAA) does not include it on their banned-substance list. PURPOSE: This study examined the effect of body-weight dosing of PSE on 800-m-run times of NCAA female runners. METHODS: Fifteen NCAA female track athletes volunteered to participate in the randomized, double-blind, crossover design. Participants were given 2.5 mg/kg PSE or placebo in trials separated by a week. Ninety minutes postingestion, participants completed an 800-m individual time trial on an indoor track. Finishing time was recorded with an automated video timing device. Heart rate and anxiety state scores were recorded immediately after each trial. RESULTS: Fourteen runners completed both trials, and 1 was an outlier: N=13. Despite the dose being well above normal therapeutic levels (144±17 mg), there was no significant difference (P=.92) in 800-m times between PSE (2:39.447±9.584) and placebo (2:39.372±9.636) trials, in postexercise heart rate (P=.635; PSE=177.9±14.5 beats/min, placebo=178.4±18.5 beats/min), or in anxiety-state levels (P=.650; PSE=38.4±11.6, placebo=38.1±8.8). CONCLUSION: A 2.5-mg/kg dose of PSE had no effect on 800-m performance for female NCAA runners. More research is needed to determine if PSE should be a specified banned substance.
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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 | 0.001 |
| 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 | 0.000 |
| 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".