Verification phase as a useful tool in the determination of the maximal oxygen uptake of distance runners
Bibliographic record
Abstract
This study investigated the utility of a verification phase for increasing confidence that a “true” maximal oxygen uptake had been elicited in 16 male distance runners (mean age (±SD), 38.7 (± 7.5 y)) during an incremental treadmill running test continued to volitional exhaustion. After the incremental test subjects performed a 10 min recovery walk and a verification phase performed to volitional exhaustion at a running speed 0.5 km·h–1 higher than that attained during the last completed stage of the incremental phase. Verification criteria were a verification phase peak oxygen uptake ≤ 2% higher than the incremental phase value and peak heart rate values within 2 beats·min–1 of each other. Of the 32 tests, 26 satisfied the oxygen uptake verification criterion and 23 satisfied the heart rate verification criterion. Peak heart rate was lower (p = 0.001) during the verification phase than during the incremental phase, suggesting that the verification protocol was inadequate in eliciting maximal values in some runners. This was further supported by the fact that 7 tests exhibited peak oxygen uptake values over 100 mL·min–1 (≥ 3%) lower than the peak values attained in the incremental phase. Further research is required to improve the verification procedure before its utility can be confirmed.
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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 | 0.002 | 0.010 |
| 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 | 0.001 | 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".