Bibliographic record
Abstract
This report presents the results of an evidence-based approach to obtaining the best available information on the natural history, prevalence, incidence, diagnosis, and treatment of root caries. Searches of electronic databases produced 807 references; from these and from citations in the selected articles, a final 161 references were used. We found that the information on the natural history of the disease does not provide practitioners with probabilities of, or time estimates for, progression of the disease through stages. For patients aged thirty and older, the prevalence of root caries is roughly 20 to 22 percent less than a person's age. Severity reaches over one lesion by age fifty, two lesions by age seventy, and just over three lesions for those seventy-five and older. About 8 percent (odds of 1:11) of the population would be expected to acquire one or more new root caries lesions in one year. The accuracy of current systems of diagnosis is unknown, although color has been shown to have little validity. Using the criteria of "softness" to define active lesions has been validated by the presence of microbes in the lesion. One strong study and other studies with weaker design or shorter duration add consistent support for the use of fluorides in the remineralization of root caries. Every three-month application of chlorhexidine varnish was shown to be efficacious in one arm of one study. Evidence for restoration of root caries is tentative since the studies were of limited design and duration.
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.
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 | 0.050 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".