Between-day variability of net and gross oxygen uptake during graded treadmill walking: effects of different walking intensities on the reliability of locomotion economy
Bibliographic record
Abstract
There have been few studies of clinical relevance conducted on the reliability of walking economy. This study was designed to determine if walking economy reproducibility increases as a function of walking intensity, and if there is any advantage in expressing walking economy as net oxygen uptake (VO2) rather than gross VO2 for reproducibility purposes. Sixteen participants (9 males, 7 females; mean age, 22.3 +/- 4.3 years) performed resting, submaximal, and maximal protocols on 2 different days, under identical circumstances, within a 7 day period. The submaximal protocol consisted of five 5 min walks (4 km.h-1) at treadmill grades of 0%, 2.5%, 5.0%, 7.5%, and 10%. Findings indicate that increments of 2.5% in treadmill grade effectively increased gross and net VO2 during walks. The reliability of net and gross measures increased as a function of walking relative intensity, reporting intraclass correlation coefficients ranging from 0.89-0.94 and 0.87-0.91, respectively, and mean coefficients of variation (CV) from 7.3%-3.6% and 8.8%-4.4%, respectively. There were no significant differences between the CV for gross and for net VO2 across the spectrum of walking relative intensities. In conclusion, there is no advantage of expressing walking economy as net VO2 instead of gross VO2 for reproducibility purposes, and a single treadmill testing session at a constant speed of 4 km.h-1 is reliable for estimating group and individual walking economy, particularly at higher percent grades.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.020 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".