Does Bulk Oxygen Delivery During Forearm Exercise Predict Heavy Intensity Exercise Time To Task Failure?
Bibliographic record
Abstract
The primary role of the cardiovascular system during exercise is to deliver oxygen in proportion to the demands of the active muscle. It is well known that acute alterations in oxygen delivery within an individual alter exercise performance. However, it is not known whether differences in oxygen delivery between subjects predict differences in exercise performance. PURPOSE: To determine whether bulk oxygen delivery to the exercising limb predicts differences in time to task failure (TTF) during heavy intensity submaximal exercise in healthy individuals. METHODS: Eight recreationally active (261.57 ± 19.35 mets) healthy males (24.25 ± 8 yrs) performed rhythmic isometric handgrip contractions (30 kg - 1 s: 2 s contraction/relaxation duty cycle) until failure. Failure was defined as the inability to generate 30 kg force on three consecutive forearm contractions. Oxygen delivery to the exercising forearm was calculated based on arterial oxygen content (oxygen saturation via pulse oximeter and [hemoglobin] via venous blood sample) and continuously measured brachial artery blood flow (BABF; Doppler and Echo ultrasound) during rest and throughout exercise. RESULTS: Neither bulk oxygen delivery to the forearm nor BABF predicted any of the difference in TTF between subjects (oxygen delivery n = 6, r2 = 0.00001, P > 0.05; BABF n = 8, r2 = 0.01, P > 0.05). CONCLUSIONS: Preliminary evidence suggests that bulk blood flow and oxygen delivery to the exercising limb is not an indicator of time to task failure during high intensity forearm exercise in healthy, recreationally active individuals. This work was funded by the Natural Science and Engineering Research Council (NSERC) of Canada, Canada Foundation for Innovation and Ontario Innovation Trust Grants to M. Tschakovsky.
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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 | 0.002 |
| 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) | 0.002 | 0.001 |
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".