Third-generation vs a second-generation LED curing light: effect on Knoop microhardness.
Bibliographic record
Abstract
Third-generation light-emitting diode (LED) curing lights use several different types of LEDs within the light to deliver a broader spectral output compared with the narrower spectral output of second-generation curing lights. This study determined the benefits of this broader spectral output. A third-generation LED curing light was modified so that the 4 peripheral LEDs, which provide the lower wavelengths, could be turned on or off, allowing the light to be used as a third- or a second-generation LED curing light. Twelve composites of A2 and lighter shades were packed into molds 2 mm deep with an internal diameter of 12 mm, and then irradiated for 20 seconds. A laboratory-grade spectroradiometer was used to ensure that all the specimens received the same irradiance and total energy (16.82 J/cm2) from the curing light in both the second- and third-generation modes. The results showed the benefits of using a broader spectrum third-generation LED curing light. This light produced composites that were as hard as when the narrower spectrum second-generation LED curing light was used (P < or = .01). In 7 of the 12 resin composites, the top surface was harder when the third-generation LED curing light was used (P < or = .01).
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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) | 0.003 | 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".