Is the FTP Test a Reliable, Reproducible and Functional Assessment Tool in Highly-Trained Athletes?
Bibliographic record
Abstract
International Journal of Exercise Science 12(4): 1334-1345, 2019. The aim of the current study was to assess reliability of the Functional Threshold Power test (FTP) and the corresponding intensity sustainable for 1-hour in a “quasi-steady state”. Highly-trained athletes (n = 19) completed four non-randomized tests over successive weeks on a Wattbike; a 3-min incremental test (GxT) to exhaustion, two 20-min FTP tests and a 60-min test at computed FTP (cFTP). Power at cFTP was calculated by reducing 20-min FTP data by 5% and was compared with power at Dmax and lactate threshold (TLac). Ventilatory and blood lactate (BLa) responses to cFTP were measured to determine whether cFTP was quasi-steady state. Agreement between consecutive FTP tests was quantified using a Bland-Altman plot with 95% limits of agreement (95% LoA) set at ± 20 W. Satisfactory agreement between FTP tests was detected (95% LoA = +13 and -17 W, bias +2 W). The 60-min effort at cFTP was successfully completed by 17 participants, and BLa and ventilatory data at cFTP were classified as quasi-steady state. A 5% increase in power above cFTP destabilized BLa data (p < 0.05) and prompted VO2 to increase to peak GxT rates. The FTP test is therefore deemed representative of the uppermost power a highly-trained athlete can maintain in a quasi-steady state for 60-min. Agreement between repeated 20-min FTP tests was judged acceptable.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".