Detection of interproximal demineralized lesions on human teeth in vitro using frequency-domain infrared photothermal radiometry and modulated luminescence
Bibliographic record
Abstract
Frequency-domain photothermal radiometry (FD-PTR or PTR) is used to detect mechanical holes and demineralized enamel in the interproximal contact area of extracted human teeth. Thirty-four teeth are used in a series of experiments. Preliminary tests to detect mechanical holes created by dental burs and 37% phosphoric acid etching for 20 s on the interproximal contact points show distinct differences in the signal. Interproximal contact areas are demineralized by using a partially saturated acidic buffer system. Each sample pair is examined with PTR before and after micromachining or treating at sequential treatment periods spanning 6 h to 30 days. Dental bitewing radiographs showed no sign of demineralized lesion even for samples treated for 30 days. Microcomputer tomography (micro-CT), transverse microradiography (TMR), and scanning electron microscopy (SEM) analyses are performed. Although micro-CT and TMR measured mineral losses and lesion depths, only SEM surface images showed visible signs of treatment because of the minimal extent of the demineralization. However, the PTR amplitude increased by more than 300% after 80 h of treatment. Therefore, PTR is shown to have sufficient contrast for the detection of very early interproximal demineralized lesions. The technique further exhibits excellent signal reproducibility and consistent signal changes in the presence of interproximal demineralized lesions, attributes that could lead to PTR as a reliable probe to detect early interproximal demineralization lesions. Modulated luminescence is also measured simultaneously, but it shows a lower ability than PTR to detect these interproximal demineralized lesions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".