Light-curing units used in dentistry: factors associated with heat development—potential risk for patients
Bibliographic record
Abstract
OBJECTIVES: To investigate how heat development in the pulp chamber and coronal surface of natural teeth with and without cusps subjected to irradiance using light-emitting diode (LED)-light-curing units (LCUs) is associated with (i) irradiance, (ii) time, (iii) distance, and (iv) radiant exposure. MATERIALS AND METHODS: Three different LED-LCUs were used. Their irradiance was measured with a calibrated spectrometer (BlueLight Analytics Inc., Halifax, Canada). An experimental rig was constructed to control the thermal environment of the teeth. The LED-LCU tip position was accurately controlled by a gantry system. Tooth surface temperature was measured by thermography (ThermaCAM S65 HS, FLIR Systems, Wilsonville, USA) and pulp chamber temperature with a thermocouple. LED-LCU tip distance and irradiation times tested were 0, 2, and 4 mm and 10, 20, and 30 s, respectively. Ethical permission was not required for the use of extracted teeth. RESULTS: Maximum surface and pulp chamber temperatures were recorded in tooth without cusps (58.1 °C ± 0.9 °C and 43.1 °C ± 0.9 °C, respectively). Radiant exposure explained the largest amount of variance in temperature, being more affected by time than irradiance. CONCLUSIONS: At all combinations of variables tested, repeated measurements produced consistent results indicating the reliability of the method used. Increased exposure time seems to be the factor most likely to cause tissue damage. CLINICAL RELEVANCE: ). Clinicians should be aware of LED-LCU settings and possible high temperature generated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".