Attenuation in Weight Gain with High Calcium- and Dairy-Enriched Diets Is Not Associated with Taste Aversion in Rats: A Comparison with Casein, Whey, and Soy
Bibliographic record
Abstract
A systematic evaluation of the effects of calcium (Ca) and protein source on food intake and taste aversion (TA) in rats is lacking. The purpose of this research was twofold: (1) to determine if Sprague-Dawley rats display TA to standard rat chow supplemented with 2.4% Ca and (2) to determine if short (24-hour) and long-term (weekly) food intake and weight gain are altered when rats are given access to diets containing various protein sources (casein, whey, dairy, or soy). Rats were assigned to one of two diet groups to examine high (2.4%) versus low (0.67%) Ca or to one of four groups to examine taste preference of diets where the sole protein was one of casein, soy, whey, or complete dairy. A crossover design was used to ensure rats consumed all test diets. Food intake and behavioral sequence of satiety were measured. There was no TA to the 2.4% Ca diet or to any protein source. Food intake did not differ between the two Ca diets or between the four protein diets. The dairy diet attenuated weekly weight gain compared to all other diets except whey. Overall, this study suggests that the levels of Ca and types of protein used in previous work addressing changes in body weight in rats do not influence food intake or trigger TA.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".