Influence of Knowledge of Sprint Number on Pacing during Repeated-Sprint Exercise
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Bibliographic record
Abstract
PURPOSE: The anticipation of exercise-induced stress influences performance during continuous exercise. However, not all exercise is continuous. This study explores the influence of prior knowledge of sprint number on mechanical work, surface EMG, and RPE during repeated-sprint exercise (RSE). METHODS: Fourteen athletes performed three RSE in random order. In one trial, subjects were informed that they would perform ten 6-s cycle sprints (with 24 s of rest) and then completed 10 sprints (control trial, CL). In a second trial, subjects were told to perform five sprints, but after the fifth sprint, they were asked to perform an additional five sprints (deception trial, DC). In a third trial, subjects were not told how many sprints they would be performing but were stopped after 10 sprints (unknown trial, UN). Data were recorded for every sprint. RESULTS: Both the initial sprint work and work accumulated during the first five sprints were greater (6.5%, P < 0.05) in the DC than in the CL and UN trials. Furthermore, the work accumulated during the ten sprints was lower (4.0%, P < 0.05) in the UN trial than in the two other trials. The EMG was greater (P < 0.05) in the DC than in the CL and UN trials during the initial sprint (8.8%) and during the first five sprints (9.1%). The sprint-induced decrease in EMG and work occurred earlier in the UN trial compared with the CL and DC trials. The RPE profile was similar in all trials. CONCLUSIONS: Results demonstrate that pacing occurs during short repeated-sprint efforts in anticipation of the number of sprints that are included in the trial.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it