Effect of Physical Exercise on Taste Perceptions: A Systematic Review
Bibliographic record
Abstract
The effect of physical exercise on nutrition has gained substantial interest in the last decade. Meaningful results have been produced concerning the effect of physical exercise on different appetite hormones and food choice/preference. While it is well known that taste and nutrition are related, the relation between taste and physical activity has not yet been fully explored. This systematic review aims to provide a detailed view of the literature on physical exercise and its effect on taste perceptions. Five tastes were included in this review: sweet, salty, bitter, sour, and umami. Sweet taste intensity, sensitivity, and preference were increased by acute physical exercise, but sweet preference was reduced by chronic physical activity. Perceived intensity and sensitivity decreased overall for salty taste, but an increased preference was noted during/following exercise. Sour taste intensity ratings were decreased following exercise and preference was enhanced. Umami taste intensity and sensitivity increased following exercise and preference was decreased. No significant results were obtained for bitter taste. While evidence regarding the effect of exercise on taste has arisen from this review, the pre-testing nutrition, testing conditions, type of test, and exercise modality must be standardized in order to produce meaningful and reproducible results in the future.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".