Effect of a Season of Play on Lactate Response in Canadian Female University Hockey Players
Bibliographic record
Abstract
1438 The lactate response of female ice hockey players has not been investigated. Lactate production and clearance is important in ice hockey where an on-ice “shift” can last 45 – 90 seconds of high intensity work, followed by 2 – 6 minutes of passive recovery. Understanding lactate response over a season of play can help coaches, physiologists, and players' design training programs to enhance performance. PURPOSE: The purpose of this study was to investigate blood lactate production and recovery, over a season of play, of Canadian Female University hockey players. METHODS: Eighteen players volunteered for the study (age 22.00 ± 0.65 yrs., height 170.05 ± 4.66 cm, body mass 67.22 ± 4.23 kg., playing experience 13.21 ± 2.65 yrs). A modified repeat sprint skate test (MRS) (Bracko and George, 2001) was used pre, mid, and post-season to elicit lactate production. Post-test finger stick was taken for blood lactate determination (Lactate Pro lactate analyser) within one minute of completion of the MRS; recovery lactate was determined following a 5 – 6 minute passive recovery. Data were analysed using Proc Mixed in SAS to estimate linear growth curves for post-MRS and recovery lactate scores. RESULTS: For each test (pre, mid, and postseason) recovery lactates were significantly (p<0.0317) lower than post-MRS lactates (post-MRS − recovery lactates: pre 12.9 − 11.9 mmol L-1, mid 12.7 − 11.5 mmol L-1, post 12.9 − 11.3 mmol L-1). Post-MRS lactate production did not change from pre, mid, to post-season. Lactate recovery did not change from pre, mid, to post-season testing. The difference between posttest and recovery lactate stayed the same for all (or each) testing session. CONCLUSIONS: These data suggest the lactate response in high-level female hockey players did not change over a season of play.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".