Does True Inter-Individual Variability Exist in Individual Responses After Endurance Training?
Bibliographic record
Abstract
Introduction: Despite the apparent existence of individual responses, it remains unknown whether the variability observed in peak oxygen consumption (VO2peak) and work rate at onset of blood lactate (OBLAWR) response following exercise training reflects true inter-individual differences. To date, few studies include a non-exercise control group to determine the impact of random/measurement error on the variability associated with VO2peak and OBLAWR responses to endurance training. Therefore, the purpose of this study was to determine whether true individual differences exist in responses to training by assessing whether the variability in VO2peak and OBLAWR responses following training exceeded the variability in a non-training control group. Methods: 16 recreationally active males completed two incremental ramp tests to determine VO2peak and OBLAWR. Participants were assigned into the control group (n = 7) or the training group (n = 9; endurance training: 30 minutes of 65% of work rate at VO2peak, four times per week) in a manner to counterbalance baseline VO2peak measures. Results: VO2peak increased significantly (p < 0.05) (+338 ± 416.2 mL/min/kg) and OBLAWR (+32.1 ± 29.2 W) increased following endurance training. The SD in change scores was greater in the training group for VO2peak and OBLAWR than the parallel control group. Specifically, this resulted in large and moderately-large effect sizes at respective values of 0.6 for VO2peak and 0.5 for OBLAWR. Conclusion: Although these preliminary results may suggest that the variability in VO2peak and OBLAWR responses to endurance training reflect true inter-individual variability beyond random/measurement error, a definitive conclusion can be made upon the completion of the study.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".