Bibliographic record
Abstract
OBJECTIVES: This study evaluated the depth of cure (DoC) of eight resin-based composites (RBCs) photocured using one multipeak light-curing unit (LCU) on the standard output setting for the manufacturer's RBC recommended exposure time and at a higher irradiance for 3 seconds. METHODS: Three conventional RBCs: Tetric EvoCeram (Evo), Tetric N-Ceram (Cer), Tetric Prime (Pri); and five bulk-fill: Tetric N-Ceram Bulk Fill (CerBF), Opus Bulk Fill APS (OpusBF), Opus Bulk Fill Flow APS (OpusF), Tetric PowerFill (PFill) and Tetric PowerFlow (PFlow) were examined. Only PFill and PFlow are formulated to be photocured in 3 seconds. The RBCs were packed into a metal mold and photocured using a Bluephase PowerCure LCU for the RBC manufacturer's recommended exposure time on the standard mode and using the 3-second high irradiance mode. After photocuring, the specimens were immersed in a solvent for 1 hour. The length of the remaining RBC was measured and divided by 2. Data were analyzed using two-way analysis of variance (ANOVA) followed by the Tukey post hoc multiple comparison test (α=0.05). RESULTS: There was no significant difference in the DoC values for PFill and PFlow when photocured using the 3-second high irradiance protocol compared to the lower irradiance standard mode protocol. All other RBCs had significantly lower DoC values (p<0.001) when photocured off-label using the 3-second high irradiance mode. CONCLUSION: Of the eight RBCs tested, only PFill and PFlow achieved the same DoC when the high irradiance 3-second curing method was used compared to when their longer lower irradiance protocol was used.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.410 | 0.246 |
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".