Caffeine increases endurance and attenuates force sensation during submaximal isometric contractions
Bibliographic record
Abstract
Caffeine has known ergogenic effects, some of which have been observed during submaximal isometric contractions. We used 15 subjects in a randomized, double-blind, repeated-measures experiment to determine caffeine's ergogenic effects on neuromuscular variables that would contribute to increased endurance capacity. Subjects performed repeated submaximal (50% maximal voluntary contraction) isometric contractions of the right quadriceps to the limit of endurance (T(lim)) 1 h after oral caffeine administration (6 mg/kg). Time to reach T(lim) increased by 17 +/- 5.25% (P < 0.02) after caffeine administration compared with the placebo trial. The changes in contractile properties, motor unit activation, and M-wave amplitude that occurred as the quadriceps reached T(lim) could not account for the prolonged performance after caffeine ingestion. In a separate experiment with the same subjects, we used a constant-sensation technique to determine whether caffeine influenced force sensation during 100 s of an isometric contraction of the quadriceps. The results of this experiment showed that caffeine reduced force sensation during the first 10-20 s of the contraction. The rapidity of this effect suggests that caffeine exerts its effects neurally. Based on these data, the caffeine-induced increase in T(lim) may have been caused by a willingness to maintain near-maximal activation longer because of alterations in muscle sensory processes.
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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".