GENDER DIFFERENCES IN SUBSTRATE OXIDATION DURING SUBMAXIMAL DYNAMIC EXERCISE
Bibliographic record
Abstract
Some, but not all studies, have reported gender differences in the metabolic response to endurance exercise. With careful gender matching and control for diet and menstrual cycle many studies have demonstrated that females oxidize more lipid and less carbohydrates than males. To more accurately address the question of gender differences in metabolism we have under-taken a meta-analysis and have combined the data from nine studies completed in our laboratory examining metabolism during endurance exercise (60–70% VO2max) in women (N = 85) carefully matched to men (N = 88). The subjects ages were similar (M = ∼24 years; F = ∼23 years), males were heavier and taller, had a lower percent body fat (M = ∼13.4 ± 4.7%; F = 22.8 ± 4.9%), and VO2max in ml/kg fat free mass/minute were similar (M = 64.8 ± 10.2; F = 61.2 ± 10.4). Resting RER was identical, yet females had a lower RER during exercise (60–90 minutes of duration) as compared to males (P < 0.0001).Table: No Caption AvailablePlasma free fatty acids at rest and during exercise were higher in females as compared to males (P < 0.01) and plasma glycerol was higher in females vs. males (P < 0.05) later in exercise. Plasma glucose and lactate were not different between the sexes. In summary, these data show that during submaximal endurance exercise, females oxidize proportionately more lipid and less carbohydrate as compared to males and this is associated with the higher plasma free fatty acid and glycerol concentrations. Supported by NSERC (Canada).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".