Impact of light-curing distance on the effectiveness of cure of bulk-fill resin-based composites
Bibliographic record
Abstract
OBJECTIVE: To investigate the effect of light-curing distance on the effectiveness of cure (EC) of bulk-fill resin-based composites (RBCs). MATERIALS AND METHODS: Two bulk-fill RBCs (a Tetric N-Ceram Bulk Fill (TN) and a Filtek Bulk Fill (FK)) are evaluated. Specimens (4 mm high) are cured for 20 s at different distances (0 mm (D0), 2 mm (D2), 4 mm (D4), 6 mm (D6) and 8 mm (D8)) and stored for 24 h in 100% relative humidity at 37 °C. The top and bottom surface hardness (SH) (n = 12) are assessed using a Knoop microhardness tester and the EC is calculated. The EC is characterized by the hardness ratio (HR) (mean bottom: top SH). An HR of 0.8 is used as the benchmark for an effective/adequate cure. Data are analyzed using one-way analysis of variance and Tukey's post hoc test (α = 0.05). Correlations between the top and bottom surfaces are examined using the Pearson correlation (α = 0.05). RESULTS: For the TN, the HR at D8 is significantly lower than all other light-curing distances, while for the FK, it is significantly lower than D0 only. CONCLUSION: The effect of light-curing distance on the EC of bulk-fill RBCs is material dependent. Notwithstanding the light-curing distance, the EC of the FK and TN is below the threshold HR value of 0.8 when photopolymerized for 20 s in 4 mm increments in black opaque molds.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".