The Lactate Minimum Test for Cycling: Estimation of the Maximal Lactate Steady State
Bibliographic record
Abstract
This study evaluated the reliability and validity of the lactate minimum test (LMT), an incremental test given after lactic acidosis was induced by sprint exercise. This test is purported to accurately estimate the intensity of exercise at which the transport of lactate into and out of the blood is in equilibrium (maximal lactate steady state or MLSS) and should be a good predictor of endurance performance. Fourteen athletes (mean age 27.2 +/- 3.7 yrs) completed the following on Kreitler rollers: (a) two 20-km time-trials (35.1 +/- 3.3 and 35.7 +/- 3.5 km.hr-1, p < .05); (b) two LMTs yielding lactate minimum speeds (LMS) of 33.6 +/- 3.4 and 33.4 +/- 3.1 km.hr-1 (p > 0.6); and (c) four constant intensity rides, at speeds bracketing the LMS. At 33.5 +/- 3.1 km.hr-1 plasma lactate concentration decreased 0.4 +/- 1.6 mM from 10 to 30 min. Plasma lactate increased 1.6 +/- 0.7 mM while riding 0.9 +/- 0.9 km.hr-1 faster. The LMT is a reliable (r2 = 0.904) and valid method to predict MLSS and a good predictor of endurance performance (LMT vs. 20-km time-trial, r2 = 0.86).
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".