Anaerobic Threshold: The Concept and Methods of Measurement
Bibliographic record
Abstract
The anaerobic threshold (AnT) is defined as the highest sustained intensity of exercise for which measurement of oxygen uptake can account for the entire energy requirement. At the AnT, the rate at which lactate appears in the blood will be equal to the rate of its disappearance. Although inadequate oxygen delivery may facilitate lactic acid production, there is no evidence that lactic acid production above the AnT results from inadequate oxygen delivery. There are many reasons for trying to quantify this intensity of exercise, including assessment of cardiovascular or pulmonary health, evaluation of training programs, and categorization of the intensity of exercise as mild, moderate, or intense. Several tests have been developed to determine the intensity of exercise associated with AnT: maximal lactate steady state, lactate minimum test, lactate threshold, OBLA, individual anaerobic threshold, and ventilatory threshold. Each approach permits an estimate of the intensity of exercise associated with AnT, but also has consistent and predictable error depending on protocol and the criteria used to identify the appropriate intensity of exercise. These tests are valuable, but when used to predict AnT, the term that describes the approach taken should be used to refer to the intensity that has been identified, rather than to refer to this intensity as the AnT.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".