Effect of Eating Cheese on Ca and P Concentrations of Whole Mouth Saliva and Plaque
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A study was undertaken to examine the release of calcium and phosphate from cheese during mastication. Unstimulated saliva was collected for baseline analysis in the initial study followed by saliva collection after chewing different cheeses with and without biscuits. In the second study, volunteers who had abstained from tooth cleaning for 24 h had plaque samples taken from two quadrants, they then chewed cheese in their own personal eating manner, and a second sample of plaque was taken within 5 min. The results showed that the calcium ion concentration of the oral fluids rose from a mean of 30 micrograms/ml to between 200 and 540 micrograms/ml, depending on the type of cheese, but the phosphate concentration fell below baseline. The release of both ions tended to be less when the cheese was eaten with a biscuit. In the second study a highly significant rise in plaque calcium concentration was shown after eating cheese, but no consistent change in phosphate level was found. Acidic soft drinks, following eating, tended to reduce the plaque calcium levels, but no consistent change was found if tea or coffee was taken following the cheese consumption. It is suggested, from these findings, that cheese eaten alone at the very end of a meal raises plaque calcium and might be effective in reducing dental caries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it