Heart rate recovery after aerobic and anaerobic tests: is there an influence of anaerobic speed reserve?
Bibliographic record
Abstract
The present study assessed if differences in the metabolic profile, inferred from the anaerobic speed reserve (ASR), would influence the dynamics of heart rate recovery (HRR) after two modes of exercise. Thirty-nine physical education students (14 females and 25 males) volunteered for this study. Participants carried out three separate testing sessions to assess maximal sprinting speed (MSS, 1st session), repeated sprint ability (RSA, 2nd session) and maximal aerobic speed (MAS) using the Université of Montreal Track Test (UMTT, 3rd session). ASR was defined as the difference between MSS and MAS. Heart rate was continuously registered throughout the tests and during the 5-min post-test recovery. To evaluate the influence of ASR on post-exercise, HRR comparisons between ASR-based groups [high ASR vs. low ASR] and sex groups (males vs. females) were performed. Significant differences (P < 0.05) were found between high ASR and low ASR groups of the same sex for indices of relative HRR after the RSA and UMTT. In addition, after the RSA test, males from the high ASR group had a significantly slower HRR kinetics compared with the males of the low ASR (P < 0.05) and the females of high ASR (P < 0.05); whereas females of the high ASR groups had a faster HRR kinetics compared with the females of low ASR group (P < 0.05). Our results showed that in males, post-exercise HRR could be related to the ASR, whereas in females, the influence of ASR is less clear.
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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 | 0.001 | 0.003 |
| 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".