A Pilot Study: Soy protein may help decrease energy intake when consumed prior to meal
Bibliographic record
Abstract
Protein & fiber reduce subjective appetite ratings acutely, leading to subsequent decreased energy intake in studies with large amounts of protein & fiber. The objective of this study was to measure satiety & energy intake following consumption of snack bars containing modest quantities of soy protein, SP, (20 g), & soy fiber, SF, (8 g) and in combination. In a randomized, double blind crossover design, 40 healthy subjects were assigned to 4 treatments with 4 types of snack bars: Control (C), SP, SF, & SP + SF. Appetite effects & bar palatability (Visual Analog Scale) & post‐meal ad libitum energy intake were measured. Subjects were asked to consume 1 type of bar within 15 mins at each visit (1‐week washout between visits). Overall appetite scores were not significantly different; however, SP tended to decrease post‐meal ad libitum energy intake vs C (−43 kcal). C bars took a significantly longer time to consume than SP or SF bars (10.3 min vs. 7.7 & 8.4 min, respectively). A post hoc sensory analysis of the bars, showed significantly different chewing attributes. The lower energy intake in the SP group is consistent with previous studies & may have long term benefits.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".