Opalescence and Fluorescence of 46 Resin-Based Composites Exposed to Ultraviolet Light
Bibliographic record
Abstract
Identifying the boundary between the tooth and the resin-based composite (RBC) is difficult when replacing restorations. Ultraviolet (UV) light has been reported to assist the viewer by causing the RBC to fluoresce. Using a laboratory-grade fiberoptic spectrometer, 46 RBCs were exposed to UV light from the Woodpecker O-Star curing light. The opalescence and fluorescence were measured relative to a human tooth that contained just dentin and a tooth that contained both enamel and dentin. After these quantitative measurements, 10 RBCs with large differences in light emittance were compared qualitatively to assess their brightness when exposed to UV light compared to the dentin specimen and the specimen containing both enamel and dentin. It was found that, when exposed to UV light, some of the RBCs were less bright compared to the two samples of teeth used for comparison, but most were brighter; some were up to six times brighter. The filler appears to affect the opalescence peaks, while the resin appears to affect the fluorescence peaks. It was concluded that because RBCs emit very different levels of opalescence and fluorescence, UV light from the Woodpecker O-Star cannot be relied upon to detect all brands of RBC on the tooth. The opalescence and fluorescence can also be used to detect changes in the formulation of the RBC.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".