Effects of Nine Different Chewing-Gums and Lozenges on Salivary Flow Rate and pH
Bibliographic record
Abstract
The objectives of this study were to determine how salivary flow rate and pH vary with time during use of chewing-gums and lozenges. Twenty-four young adults collected unstimulated saliva and then, on different occasions, chewed one of six flavoured gums, or gum base, or sucked on one of two lozenges, for 20 min, during which time eight separate saliva samples were collected. Flow rate peaked during the 1st minute of stimulation with all nine products. With the lozenges, flow rate fell towards the unstimulated rate when the lozenges had dissolved. There were no significant differences in the flow rates elicited by cinnamon- or peppermint-flavoured gums or between sugar-containing or sugar-free gums. With the flavoured gums, the mean flow rate followed a power curve (r = -0.992) with time and within about 10 min was not significantly different from that when gum base was the stimulus. The initial stimulated flow rate with flavoured gums was about 10-12 times greater than the unstimulated rate (0.47 ml/min). After 20 min of chewing, it was still about 2.7 times that rate and about the same as the flow rate elicited by chewing-gum base alone. The pH of unstimulated saliva was about 6.95. With one gum containing about 1.5% organic acids, the salivary pH fell to a minimum of 6.18 in the 1st minute of stimulation, but then rose rapidly to a level above that in unstimulated saliva. With a sucrose-containing and a sucrose-free gum, the pH rose immediately on stimulation and then fell slightly with time to levels which were significantly above the pH of unstimulated saliva.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".