Intensity and appreciation of sweet taste solutions are modulated by high-intensity aerobic exercise in adolescent athletic males
Bibliographic record
Abstract
Abstract Introduction Exercise tends to reduce subsequent meal intake, but mechanisms are still unclear. Interestingly, exercise seems to influence taste, which plays a role in energy intake. The effect of exercise on specific tastes is still to be elucidated, especially among younger participants who train at high intensity. Methods Adolescents (14-16 years old) were recruited from a high school boys hockey team. Distinct taste tests were administered using low and high concentrations of sweet (sucrose 41.0 & 82.0 g/L), salty (sodium chloride 8.7 & 17.4 g/L) and bitter (caffeine 5.0 & 10.0 g/L) solutions before and after a 30 min aerobic high-intensity exercise session (70-90% of estimated maximal heart rate). McNemmar’s tests, standard paired T tests, Wilcoxon Signed Rank Test and Cohen’s d effect size tests were used to analyze the data. Results Participants (n=19) were 14.7±0.7 years old, weighed 59.6±7.8kg, had a height of 173.4±7.9cm, and a bodyfat% of 11.6±3.1%. There were no significant differences in taste identification capacities. Participants (n=19) perceived as more intense (+31%, p=0.037) and appreciated better the low concentration sweet solution (+20%, p=0.004). Taste appreciation was also increased for the high concentration sweet solution (+15%, p=0.009). Effect sizes were medium [0.516-0.776]. Conclusion High-intensity exercise influenced the perception of sweet taste. If higher taste intensity and appreciation of sweet can reduce energy intake, our results could help explain the effect of exercise on lowering subsequent energy intake.
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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) | 0.003 | 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".