Near‐UV laser treatment of extrinsic dental enamel stains
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The selective ablation of extrinsic dental enamel stains using a 400-nm laser is evaluated at several fluences for completely removing stains with minimal damage to the underlying enamel. STUDY DESIGN/MATERIALS AND METHODS: A frequency-doubled Ti:sapphire laser (400-nm wavelength, 60-nanosecond pulse duration, 10-Hz repetition rate) was used to treat 10 extracted human teeth with extrinsic enamel staining. Each tooth was irradiated perpendicular to the surface in a back-and-forth motion over a 1-mm length using an ∼300-µm-diam 10th-order super-Gaussian beam with fluences ranging from 0.8 to 6.4 J/cm(2) . Laser triangulation determined stain depth and volume removed by measuring 3D surface images before and after irradiation. Scanning electron microscopy evaluated the surface roughness of enamel following stain removal. Fluorescence spectroscopy measured spectra of unbleached and photobleached stains in the spectral range of 600-800 nm. RESULTS: Extrinsic enamel stains are removed with laser fluences between 0.8 and 6.4 J/cm(2) . Stains removed on sound enamel leave behind a smooth enamel surface. Stain removal in areas with signs of earlier cariogenic acid attacks resulted in isolated and randomly located laser-induced, 50-µm-diam enamel pits. These pits contain 0.5-µm diam, smooth craters indicative of heat transfer from the stain to the enamel and subsequent melting and water droplet ejection. Ablation stalling of enamel stains is typically observed at low fluences (<3 J/cm(2) ) and is accompanied by a drastic reduction in porphyrin fluorescence from the Soret band. CONCLUSION: Laser ablation of extrinsic enamel stains at 400 nm is observed to be most efficient above 3 J/cm(2) with minimal damage to the underlying enamel. Unsound underlying enamel is also observed to be selectively removed after irradiation.
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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) | 0.000 | 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) | 0.002 | 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".