Mechanical, Metabolic and Perceptual Response during Sprint Training
Bibliographic record
Abstract
This study aimed to analyze perceptual, metabolic and mechanical responses to sprint training sessions. 9 male high-level sprinters performed 40 m running sprints up to a loss of 3% in speed, with 4 min rests between sets. Perceptual (rating of perceived exertion, RPE), mechanical (speed and countermovement jump height loss) and metabolic (blood lactate and ammonia) parameters were measured pre-exercise and after each sprint was performed. Relationships between the variables were calculated with a 90% confidence interval. Jump height loss showed almost perfect relationships with both blood lactate (r=0.96 (0.95 to 0.97)) and ammonia (r=0.95 (0.94 to 0.95)), whereas speed loss, number of sprints performed and RPE values showed large-very large relationships with blood lactate and ammonia. Furthermore, an almost perfect curvilinear relationship was observed between lactate and ammonia concentrations (R(2)=0.96 (0.95 to 0.97)). These results suggest that countermovement jump (CMJ) height can be used to quantify the fatigue induced during a typical sprint training session, and may prove a useful tool to facilitate individualized load monitoring. The results indicate that the CMJ is a better monitor of metabolic fatigue than traditional measures.
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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) | 0.001 | 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".