Maximum tolerable dose of red pepper decreases fat intake independently of spicy sensation in the mouth
Bibliographic record
Abstract
Dietary red pepper suppresses energy intake and modifies macronutrient intake. We have investigated whether a stimulus in the mouth and the sensation of spiciness are necessary for red pepper-induced changes in energy and macronutrient intake in human volunteers. In a preliminary test, sixteen Japanese male volunteers tasted samples of a soup with graded doses of red pepper in order to define a moderate and a maximum tolerable (strong) dose of red pepper. On the day of the experiment, a standardised breakfast was given to the volunteers. At lunchtime, the subjects ingested one of four experimental soups containing either a placebo, a moderate or a strong dose of red pepper plus placebo capsules, or a placebo soup plus capsules delivering a strong dose of red pepper. The rest of the meal was given ad libitum to all subjects. The amount of food, protein and carbohydrate ingested was similar for all conditions. Energy and fat intake were similar after the ingestion of the moderate soup compared with placebo. However, the strong soup significantly lowered fat intake compared with placebo (P=0.043), and ingestion of strong capsules also tended to suppress it (P=0.080). Moreover, energy intake after strong soup and capsules tended to be lower than placebo (P=0.089 and 0.076, respectively). The present results indicate that the maximum tolerable dose is necessary to have a suppressive effect of red pepper on fat intake. The main site of the action of red pepper is not in the mouth.
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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) | 0.002 | 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".