Why does supragingival calculus form preferentially on the lingual surface of the 6 lower anterior teeth?
Bibliographic record
Abstract
Many authors have assumed that the reason supragingival calculus tends to form preferentially on the lingual surface of the 6 lower anterior teeth is because saliva from the adjacent submandibular ducts is a source of calcium and phosphate ions and because loss of CO2 as the saliva enters the mouth increases the local pH. However, the fluid phase of plaque in all locations is supersaturated with respect to the calcium phosphates in calculus and there is always a tendency for calculus to deposit, except after sugar consumption, when plaque pH may fall below the critical level and the plaque fluid becomes unsaturated. pH is least likely to fall below the critical level in plaque lingual to the lower anterior teeth, as this plaque is very thin, sugar concentration after sugar intake is lowest in that area and its clearance rate is fastest, and the high salivary film velocity there promotes loss of any acid formed in plaque. A high salivary film velocity also brings more salivary urea to the site, which facilitates plaque alkalinization. These factors all contribute to the development of shallow Stephan curves of short duration and together provide a more reasonable explanation for the fact that supragingival calculus deposition progresses most easily on the lingual surface of the lower anterior teeth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".