The Efficacy of LED Light Polymerization Units in Private Dental Offices in Toronto, Canada
Bibliographic record
Abstract
Light-emitting-diode (LED) light-polymerization units (LPUs) are currently routinely used for resin-based composites (RBC) photopolymerization. This study aimed to determine the effectiveness of LED-LPUs used in participating private dental practices in Toronto, Canada. One-hundred dental practices were recruited, and 113 LED-LPUs were examined. Part 1 evaluated radiant exposure (RE) of participants’ LED-LPUs. Majority of LPUs (n=87, 77%) passed the study-required criterion (delivering equivalent to 16 J/cm2 in 20s). A strong, negative correlation between LPUs' age, light-probe damage, and RE was found. Part 2 evaluated operator's technique to deliver 8 J/cm2 of RE in 10s to simulated restorations before and post-instructional. Before instructions, 73.6% of participants delivered required-energy to anterior restoration, and 32.2% of participants delivered required-energy to posterior restoration. Following instructions, 94.3% of participants delivered required-energy to anterior restoration, and 73.6% of participants delivered required-energy to posterior restoration. Part 3 examined relative-hardness (RH) of two RBCs polymerized at 1mm and 4mm, tip-to-target distance. Both RBCs polymerized at 1mm had average RH (ratio of mean lower/upper surface hardness) greater than 0.80, but not at 4mm tip-to-target distance. Part 4 evaluated the diametral tensile strength (DTS) of two RBCs polymerized with participating LED-LPUs. No significant difference between mean DTS values of two RBCs was observed. Mean DTS values were highly correlated among the LED-LPUs tested. In conclusion, 23% of LED-LPUs tested were deemed as incompetent for sufficient RBC polymerization. A high percentage of dental practitioners failed to deliver 8 J/cm2 in 10s exposure cycle, even after receiving specific instructions (5.7% to anterior restoration and 26.4% to posterior restoration). The outcome was due to a combination of LPUs performance and operator's technique. This finding is alarming as it relates well to early failure of Class-2 RBC restorations due to insufficient polymerization.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".