Irradiance Uniformity and Distribution from Dental Light Curing Units
Bibliographic record
Abstract
PROBLEM: The irradiance from dental light-curing units (LCUs) is commonly reported as a single number, but this number does not properly describe the light output. PURPOSE: This study examined the irradiance uniformity and distribution from a variety of LCUs as well as the effect of different light guides. MATERIALS AND METHODS: Five LCUs representing quartz-tungsten-halogen, plasma arc, and light emitting diode units were evaluated. One LCU was evaluated using two different light guides (Standard or Turbo style). The total power emitted from each LCU was measured and the irradiance calculated using conventional methods (I(CM)). In addition, a beam profiler was used to determine the optically active emitting area, the mean irradiance (I(BP)), the irradiance distribution, and the Top Hat Factor (THF). Five replications were performed for each test and compared using analysis of variance with Fisher's PLSD tests at a pre-set alpha of 0.05. RESULTS: The spatial distribution of the irradiance from LCUs was neither universally symmetrical nor was it uniformly distributed across the tip end. Significant differences in both the emitted power and THF were found among the LCUs. The THF values ranged from a high of 0.74 +/- 0.01 to a low of 0.32 +/- 0.01. Changing from a standard to a turbo light guide increased the irradiance, but significantly reduced beam homogeneity, reduced the total emitted power, and reduced the optical tip area by 60%. CONCLUSIONS: Using different light guides on the same LCU significantly affected the power output, irradiance values, and beam homogeneity. For all LCUs, irradiance values calculated using conventional methods (I(CM)) did not represent the irradiance distribution across the tip end of the LCU. CLINICAL SIGNIFICANCE Irradiance values calculated using conventional methods assume power uniformity within the beam and do not validly characterize the distribution of the irradiance delivered from dental light curing units.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".