Effect of damage or contamination to the tips of 200 light-curing units
Bibliographic record
Abstract
OBJECTIVE: The light-curing unit (LCU) has become a vital piece of dental equipment that must be correctly maintained. This study investigated the impact of contamination and physical damage to the light tip on the power and radiant emittance values from old and new LCUs. MATERIALS AND METHODS: Two investigators assessed 200 LCUs in dental clinics. The extent of contamination and physical damage to the light-curing unit (LCU) tips was recorded using a scale ranging from 0 to 8, where 0 indicates the absence of damage or contamination, and 8 represents severe damage or contamination. Then, the radiant emittance and power values of the LCU tip were measured using a digital radiometer (Bluephase meter II; Ivoclar, Schaan, Liechtenstein). LCUs that were more than five years old were classified as old. Spearman correlation coefficient was used to determine the relationship between the condition of the LCU and radiant emittance/power (p = 0.05). RESULTS: There were no significant differences in the percent reduction of the power and radiant emittance from the values reported by the manufacturers, as well as the presence of contamination or physical damage scores between old and relatively new light-curing tips (p > 0.05). The mean ± standard deviation percentage reductions in power and radiant emittance from the manufacturer's stated values were 19.2 ± 17.63% and 3.9 ± 16.49%, respectively. Contamination and physical damage had significant positive correlations with the reduction in the power (r = 0.22070, p = 0.0017 and r = 0.27422, p < 0.0001, respectively) and the reduction in the radiant emittance (r = 0.28626, p < 0.0001 and r = 0.36650, p < 0.0001). Increased contamination and physical damage scores corresponded to greater percent reductions in the power and radiant emittance (p < 0.05). CONCLUSIONS: Contamination and physical damage to the LCU can negatively impact the light output from LCUs. CLINICAL RELEVANCE: To ensure optimal performance, dentists should regularly monitor the output of their LCUs and examine the devices for any signs of physical damage or contamination.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".