A sub-maximal occupational aerobic fitness test alternative, when the use of heart rate is not appropriate
Bibliographic record
Abstract
UNLABELLED: Several emergency response organisations have introduced a minimum aerobic fitness test to predict performance on critical tasks, as well as to help ensure some protection against the cardiovascular stress associated with emergency situations. A popular indirect sub-maximal test of aerobic fitness is the step test; this test relies on the relationship between exercise intensity, heart rate and aerobic capacity. This relationship, and the tests that rely on it, are not valid for individuals who are on prescribed medication (often for high blood pressure) that alter the heart rate response to exercise. OBJECTIVE: The purpose of the work described in this paper was to develop a sub-maximal test of aerobic fitness that did not rely on heart rate. PARTICIPANTS AND METHODS: Eighty-four subjects undertook the Tecumseh step test and a six-minute maximal walk test. RESULTS: A Pearson Product correlation of r=- 0.81, P< 0.01 was identified between the distance that an individual could walk in six minutes and their heart rate response to the step test. CONCLUSIONS: It is concluded that the walk test offers a valid alternative to the step test for the indirect sub-maximal assessment of aerobic fitness.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".