Blood Lactate Concentration and Clearance in Elite Swimmers During Competition
Bibliographic record
Abstract
PURPOSE: Blood lactate concentration, [BLa], after swimming events might be influenced by demographic features and characteristics of the swim race, whereas active recovery enhances blood lactate removal. Our aims were to (1) examine how sex, age, race distance, and swim stroke influenced [BLa] after competitive swimming events and (2) develop a practical model based on recovery swim distance to optimize blood lactate removal. METHODS: We retrospectively analyzed postrace [BLa] from 100 swimmers who competed in the finals at the Canadian Swim Championships. [BLa] was also assessed repeatedly during the active recovery. Generalized estimating equations were used to evaluate the relationship between postrace [BLa] with independent variables. RESULTS: Postrace [BLa] was highest following 100-200 m events and lowest after 50 and 1500 m races. A sex effect for postrace [BLa] was observed only for freestyle events. There was a negligible effect of age on postrace [BLa]. A model was developed to estimate an expected change in [BLa] during active recovery (male = 0; female = 1): [BLa] change after active recovery = -3.374 + (1.162 × sex) + (0.789 × postrace [BLa]) + (0.003 × active recovery distance). CONCLUSIONS: These findings indicate that swimmers competing at an elite standard display similar postrace [BLa] and that there is little effect of age on postrace [BLa] in competitive swimmers aged 14 to 29 y.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".