Effects of pH and acid concentration on erosive dissolution of enamel, dentine, and compressed hydroxyapatite
Bibliographic record
Abstract
The aims of this study were to determine the effects of pH and acid concentration on the dissolution of enamel, dentine, and compressed hydroxyapatite (HA) in citric acid solutions (15.6 and 52.1 mmol l(-1) ; pH 2.45, 3.2, and 3.9), using a pH-stat system. After an initial adjustment period, the dissolution rates of enamel and HA were constant, while that of dentine decreased with time. The dissolution rate increased as the pH decreased, and this was most marked for enamel. To compare substrates, the rate of mineral dissolution was normalized to the area occupied by mineral at the specimen surface. For a given acid concentration, the normalized dissolution rate of HA was always less than that for either dentine or enamel. The dissolution rate for dentine mineral was similar to that for enamel at pH 2.45 and greater at pH 3.2 and pH 3.9. The concentration of acid significantly affected the enamel dissolution rate at pH 2.45 and pH 3.2, but not at pH 3.9, and did not significantly affect the dissolution rates of dentine or HA at any pH. The variation in response of the dissolution rate to acid concentration/buffer capacity with respect to pH and tissue type might complicate attempts to predict erosive potential from solution composition.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".