Comparative study of methods to evaluate depth of cure of restorative composites
Bibliographic record
Abstract
The objective of this study was to compare two methods to evaluate the depth of cure (DOC) of restorative composites and if the extension of the light-activation time would increase the DOC of composites.Two bulk-fill composites (Tetric Evoceram Bulk Fill, Ivoclar Vivadent and Filtek One Bulk Fill, 3M Oral Care) and two conventional composites (Tetric N-Ceram, Ivoclar Vivadent e Filtek Z350 XT, 3M Oral Care) were tested. Cylindrical samples were made by inserting the composites into a hole of matriz with 5 mm internal diameter and 13 mm depth, and light-activated with light curing unit from the same manufacturers of each composite, using the manufacturer recommendation time (MRT), or for double the time (DOT). Two methods compared were: 1- ISO 4049 test and 2- dissolution with organic solvent (acetone). For the ISO 4049 test, the unpolymerized resin was manually removed with a plastic spatula and the length of the samples measured with a digital caliper to calculate the DOC. In the organic solvent method, the unpolymerized resin was removed manually and samples were immersed inn the dark in acetone for 48 hours for DOC measurement. It was observed that light curing for DOT produced significantly higher DOC than those for MRT. Differences in DOC measurements between ISO and "organic solvent" methods were material dependent.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".