Failure rates among metal brackets cured with two high-intensity LED light-curing lamps: an<i>in vivo</i>study
Bibliographic record
Abstract
OBJECTIVE: The objective of this split-mouth clinical trial was to compare bonding failure rates of metal brackets bonded with two different light-emitting diode (LED) light-curing lamps with different high-intensity power outputs. MATERIALS AND METHODS: Forty patients were included for a total of 800 brackets that were randomly bonded (left and right sides in a 1:1 ratio) in maxillary and mandibular arches using two different LED devices. An LED of 3200 mW/cm2 and an LED of 5000 mW/cm2 were used in this split-mouth clinical trial. Bonding failures during the initial 6 months of orthodontic treatment were recorded as maxillary versus mandibular, anterior teeth versus posterior teeth, and left side versus right side. RESULTS: Five dropouts were recorded for discontinuing orthodontic treatment and 700 brackets were analysed in total. The bonding failure rates for 3200 and 5000 mW/cm2 LEDs were 6.0 and 7.4 per cent, respectively (P = 0.450), which were not statistically significantly different. There were no significant differences in bracket survival rates between the LEDs used (P = 0.866). The posterior teeth presented a higher index of bond failures (odds ratio, 3.14; 95% confidence interval, 1.68-5.87; P < 0.001). LIMITATIONS: Direct comparison was only done between two high-intensity LED lights rather than against conventionally used halogen lights. CONCLUSION: Similar bonding failures were recorded using both LED devices (3200 and 5000 mW/cm2). Significantly more bonding failures occurred in premolar teeth than in anterior teeth.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".