The effect of distance from light source on light intensity from curing lights.
Bibliographic record
Abstract
PURPOSE: To investigate how light intensity changes as the distance increases from the tip of the light guide. MATERIALS AND METHODS: Ten different curing light/light guide combinations were used. Light intensity was measured at 0, 3, 6, and 10 mm from the tip of the light guide with a radiometer. Measurements were repeated in five separate trials and the mean light intensity +/- standard deviation was calculated. The fiber density was measured at the entrance and exit of all ten light guides and the light dispersion patterns were recorded. RESULTS: Light intensity decreased as distance increased for all lights tested; however, the rate and extent of this decrease was not similar for all lights (p < 0.0001). Turbo light guides exhibited a more rapid decrease in intensity as the distance increased than standard light guides. At 10 mm, all the turbo light guides had lost over 80% of their intensity recorded at 0 mm. CONCLUSION: 1. The rate and extent of the decrease in intensity is not similar among curing lights (p < 0.0001). 2. It is not possible to predict light intensity at 10 mm from measurements made at 0 mm. 3. Curing light manufacturers should state intensity over clinically relevant distances (0 to 10 mm).
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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 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".