Psychophysiological response and energy balance during a 14-h ultraendurance mountain running event
Bibliographic record
Abstract
Many studies have researched the psychophysiological response and energy balance of athletes in numerous ultraendurance probes, but none has investigated an ultraendurance mountain running event. The current study aims to analyze changes in blood lactate concentration, rating of perceived exertion, heart rate, heart rate variability, and energy balance after the performance of an ultraendurance mountain running event. The parameters in the 6 participants who finished the event were analyzed (age, 30.8 ± 3.1 years; height, 176.2 ± 8.6 cm; body mass, 69.2 ± 3.7 kg). The race covered 54 km, with 6441 m of altitude change, 3556 m downhill and 2885 m uphill. The athletes completed together the race in 14 h and 6 min. After the ultraendurance event, the athletes presented a negative energy balance of 4732 kcal, a blood lactate concentration of 2.8 ± 0.3 mmol/L, a heart rate mean/heart rate maximum ratio of 0.64, a heart rate mean of 111.4 ± 5.9 beats/min, a decrease in vagal modulation, and an increase in sympathetic modulation, and recorded 19.5 ± 1.5 points on the 6-20 rating of perceived exertion scale. The event was a stressful stimulus for the athletes despite the low intensity measured by blood lactate concentration and heart rate. The results obtained may be used by coaches as a reference parameter of heart rate, heart rate variability, rating of perceived exertion, and lactate concentration to develop specific training programs. In addition, the energy balance data obtained in this research may improve nutritional intake strategies.
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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".