Effect of high irradiance and short exposure times on the depth of cure of six bulk‐fill resin composites
Bibliographic record
Abstract
This study examined the effect of high irradiance and short exposure times on the depth of cure of six resin-based composites (RBCs). Bluephase PowerCure and the Valo X light-curing units (LCUs) were used to photocure bulk-fill RBCs for their recommended exposure times: Admira Fusion x-tra (AFX/20s), Aura Bulk Fill (ABF/20s), Filtek One Bulk Fill (FOB/20s), Opus Bulk Fill APS (OBF/30s), Tetric EvoCeram Bulk Fill (TEC/10s) and Tetric PowerFill (TPF/10s). In addition, all bulk-fill RBCs were tested for depth of cure with one short 3 s exposure time from the Bluephase PowerCure or the Valo X in the Xtra Power mode. The RBCs (n = 10 per RBC) were inserted into a 4 mm diameter metal mold and covered by a polyester strip before being photocured. After 24 h of storage, uncured RBC was scraped away to determine the depth of cure of the RBCs. None of the RBCs achieved a 4 mm depth of cure. The depth of cure of TEC and TPF was unaffected by the exposure times (recommended or short) when using the Valo X. The depth of cure of AFX/20s, AFX/Xtra Power, ABF/Xtra Power, FOB/Xtra Power, and OBF/30s RBCs was greater when using Valo X compared to the Bluephase PowerCure. It was concluded that short exposure times can reduce depth of cure and should only be used for some RBCs.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".