Is the intensity of the highest fat oxidation at the lactate concentration of 2 mmol L<sup>−1</sup>? A comparison of two different exercise protocols
Bibliographic record
Abstract
BACKGROUND: The exercise intensity eliciting highest fat oxidation is important for a variety of populations and its precise determination requires an adequate exercise protocol. The aim of this study was to compare fat oxidation, concentration of lactate and lactate threshold during an established exercise protocol using fixed workloads with a protocol based upon the subject's individual heart rate response to exercise. MATERIALS AND METHODS: Highest fat oxidation, concentration of lactate and lactate threshold were compared between two different exercise protocols in moderately trained men (n = 48) and women (n = 30). In randomized order subjects completed a standardized (STAND) and an individual (IND) submaximal exercise test. The increments during IND were adapted by the subjects' individual heart rate response to exercise compared to STAND with defined steps. RESULTS: In men, fat oxidation was significantly higher at the intensity eliciting highest fat oxidation in STAND than in IND (P = 0.019), but not in women. In both genders lactate concentration (P < 0.001) and heart rate (HR) (P < 0.001) were significantly higher in IND compared to STAND at this intensity. A significant correlation between O2 at lactate threshold and the intensity eliciting the highest fat oxidation was found in both genders in IND (women r = 0.73; men r = 0.43) and in STAND (women r = 0.57; men r = 0.56). CONCLUSION: Different exercise increments and stage durations have an influence on lactate concentration and HR at the intensity eliciting the highest fat oxidation. The shorter test duration of STAND favours this protocol to determine maximal fat oxidation. For the untrained, start of exercise should be at very low intensity.
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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 | 0.000 | 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".