Anaerobic Running Capacity Determined from a 3-Parameter Systems Model: Relationship with other Anaerobic Indices and with Running Performance in the 800 m-Run
Bibliographic record
Abstract
The purpose of this study was to compare anaerobic running capacity (ARC, i.e., the distance that can be run using only stored energy sources in the muscle) determined from a 3-parameter systems model with other anaerobic indices and with running performance in the 800 m. Seventeen trained male subjects (.VO(2max) = 66.54 +/- 7.29 ml . min (-1) . kg (-1)) performed an incremental test to exhaustion for the determination of .VO(2max) and peak treadmill velocity (PTV), five randomly ordered constant velocity tests at 95, 100, 105, 110, and 120 % of PTV to compute ARC and oxygen deficit (O(2)def, at 110 % of PTV), and a 800-m time trial to determine running performance (mean velocity over the distance, V (800 m)) and peak blood lactate concentration ([La (-)] (b, peak)). ARC (467 +/- 123 m) was positively correlated with O(2)def (56.35 +/- 18.47 ml . kg (-1); r = 0.57; p < 0.05), but not with [La (-)] (b, peak) (15.08 +/- 1.48 mmol . l (-1); r = - 0.16; p > 0.05). The O(2) equivalent of ARC (i.e., the product of ARC by the energy cost of running; 103.74 +/- 28.25 ml . kg (-1)), which is considered as an indirect estimation of O(2)def, was significantly higher than O(2)def (p < 0.01, effect size = 1.99). It was concluded that ARC is partially determined by anaerobic pathway, but that it probably does not provide an accurate measure of anaerobic capacity, if, however, O(2)def can be considered as a criterion measure for it.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".