Sex Differences in the Physiological Responses’ of Elite Collegiate Hockey Players during a Submaximal Test
Bibliographic record
Abstract
To optimize the health and sport performance in athletes, sport scientists have recently turned to monitoring physiological variables and markers of performance. Currently, preferred types of monitoring have not been identified and past research has shown that males and females might react differently to physiological stress. PURPOSE: To compare the physiological response of male and female elite collegiate hockey players after a 4-minute submaximal cycling test performed at a predicted 75% of VO2max. METHODS: 52 elite Canadian collegiate hockey players, 28 males (age = 22.6±1.3, height =182.59 ±6.00 cm, weight = 87.12±6.43 kg, body fat = 17.3±4.28%) and 24 females (age = 19.9±1.3, height =166.97 ±7.20 cm, weight = 67.75±8.10kg, body fat = 26.3±4.68%) participated in a 4-minute submaximal cycling test at a predicted 75% of VO2max. Heart rate (HR) and rate of perceived exertion (RPE) were assessed during each stage and after the submaximal test, while blood lactate level was measured 2 minutes after the test. ANOVA was used to compare sex differences in HR, RPE and post exercise blood lactate. SUMMARY OF RESULTS: Females had higher heart rates at each stage of the exercise test: time 1 (F(1,51) = 5.914, p ≤ .05), time 2 (F(1,51) = 14.457, p ≤ .05), time 3 (F(1,51) = 15.299, p ≤ .05) and time 4 (F(1,51) = 14.628, p ≤ .05). There were no between sex differences in post exercise blood lactate and RPE at any stage of the exercise test. CONCLUSION: Under similar physiological stress, male and female athletes demonstrate similar post exercise blood lactate levels. However, submaximal heart rates at each stage of the submaximal test were higher among the female athletes. More work is needed to understand cardio-metabolic sex differences, which could help sport scientists better tailor training program for elite female athletes. This novel method of testing may be suitable for tracking physical fitness over the course of a playing season for male and female athletes.
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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) | 0.000 | 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) | 0.004 | 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".