A Comparison of Caffeine versus Pseudoephedrine on Cycling Time-Trial Performance
Bibliographic record
Abstract
Both caffeine (CAF) and pseudoephedrine (PSE) are proposed to be central nervous system stimulants. However, during competition, CAF is a permitted substance, whereas PSE is a banned substance at urinary levels >150 μg · ml(-1). As a result, this study aimed to compare the effect of CAF versus PSE use on cycling time trial (TT) performance to explore whether the legal stimulant was any less ergogenic than the banned substance. Here, 10 well-trained male cyclists or triathletes were recruited for participation. All athletes were required to attend the laboratory on four separate occasions--including a familiarization trial and three experimental trials, which required participants to complete a simulated 40 km (1,200 kJ) cycling TT after the ingestion of either 200 mg CAF, 180 mg PSE or a nonnutritive placebo (PLA). The results showed that the total time taken and the mean power produced during each TT was not significantly different (p > .05) between trials, despite a 1.3% faster overall time (~57 s) after CAF consumption. Interestingly, the time taken to complete the second half of the TT was significantly faster (p < .05) in CAF as compared with PSE (by 99 s), with magnitude based inferences suggesting a 91% beneficial effect of CAF during the second half of the TT. This investigation further confirms the ergogenic benefits of CAF use during TT performances and further suggests this legal CNS stimulant has a better influence than a supra-therapeutic dose of PSE.
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 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) | 0.001 | 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".