Light energy transmission through cured resin composite and human dentin.
Bibliographic record
Abstract
OBJECTIVE: This study determined the amount of light energy transmitted through various densities of cured resin composite and human dentin when 2 different light intensities were used. METHOD AND MATERIALS: The maximum light energy (mW/cm2) transmitted through disks (0.46 to 5.85 mm thick) of 7 resin composites and human dentin was measured when either a Standard or a Turbo light guide was attached to a curing light. The effects of the 2 light guides, the specimen thickness, and type of specimen dentin on light energy transmission were determined. RESULTS: The mean light energy reading at the surface of the specimens was 682.1 mW/cm2 with the Standard light guide and 1,014 mW/cm2 with the Turbo light guide. For all the specimens, there was an exponential decrease in light energy transmitted as the specimen thickness increased. The analysis of covariance showed that the specimen, thickness, and light guide all had a statistically significant effect. Significantly more light energy (about 42%) was transmitted through the specimens when the Turbo light guide was used. CONCLUSION: When the Turbo light guide was used, about 42% more light energy was transmitted through the cured composite specimens. There was an exponential decrease in the light energy transmitted through 7 resin composites and dentin as the specimen thickness increased.
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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 | 0.001 |
| 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) | 0.004 | 0.001 |
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".