Maximal power output during incremental cycling test is dependent on the curvature constant of the power–time relationship
Bibliographic record
Abstract
The aim of this study was to investigate whether the maximal power output (Pmax) during an incremental test was dependent on the curvature constant (W') of the power-time relationship. Thirty healthy male subjects (maximal oxygen uptake = 3.58 ± 0.40 L·min(-1)) performed a ramp incremental cycling test to determine the maximal oxygen uptake and Pmax, and 4 constant work rate tests to exhaustion to estimate 2 parameters from the modeling of the power-time relationship (i.e., critical power (CP) and W'). Afterwards, the participants were ranked according to their magnitude of W'. The median third was excluded to form a high W' group (HIGH, n = 10), and a low W' group (LOW, n = 10). Maximal oxygen uptake (3.84 ± 0.50 vs. 3.49 ± 0.37 L·min(-1)) and CP (213 ± 22 vs. 200 ± 29 W) were not significantly different between HIGH and LOW, respectively. However, Pmax was significantly greater for the HIGH (337 ± 23 W) than for the LOW (299 ± 40 W). Thus, in physically active individuals with similar aerobic parameters, W' influences the Pmax during incremental testing.
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 | 0.000 | 0.003 |
| 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 | 0.000 | 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".