Fluoride and Mineralized Tissues
Bibliographic record
Abstract
This review focuses on the interaction of fluoride with the material properties of bone and teeth, which is of clinical, scientific, and public health interest. These tissues are composed primarily of collagen (protein) and hydroxyapatite (mineral), and their mechanical function depends on the properties of the constituents, their proportions, the interface, and the three-dimensional structure. Changing any of these may have clinical consequences. Fluoride interacts with mineralized tissues in a number of ways. At low doses, the fluoride may be passively incorporated into the mineral, stabilizing it against dissolution; this is one of the mechanisms by which municipally fluoridated water reduces the incidence of dental caries. At higher doses, such as those used for treatment of osteoporosis, the fluoride may alter the amount and structure of tissue present, including altering the interface between the collagen and mineral. At very high doses, skeletal and dental fluorosis occurs, characterized by debilitating changes in the skeleton and by marked mottling and discoloration of teeth, which may be accompanied by increased wear of the enamel. These effects have been observed in communities where the local drinking water has naturally high fluoride levels. Understanding the influence of fluoride on mineralized tissues is, therefore, of considerable significance.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".