Changes on degree of conversion of dual-cure luting light-cured with blue LED
Bibliographic record
Abstract
The indirect adhesive procedures constitute recently a substantial portion of contemporary esthetic restorative treatments. The resin cements have been used to bond tooth substrate and restorative materials. Due to recently introduction of the self-bonding resin luting cement based on a new monomer, filler and initiation technology has become important to study the degree of conversion of these new materials. In the present work the polymerization reaction and the filler content of dual-cured dental resin cements were studied by means of infra-red spectroscopy (FT-IR) and thermogravimetry (TG). Twenty specimens were made in a metallic mold (8 mm diameter × 1 mm thick) from each of 2 cements, Panavia® F2.0 (Kuraray) and RelyX™ Unicem Applicap (3M/ESPE). Each specimen was cured with blue LED with power density of 500 mW/cm2 for 30 s. Immediately after curing, 24 and 48 h, and 7 days DC was determined. For each time interval 5 specimens were pulverized, pressed with KBr and analyzed with FT-IR. The TG measurements were performed in Netzsch TG 209 under oxygen atmosphere and heating rate of 10°C/min from 25 to 700°C. A two-way ANOVA showed DC (%) mean values statistically significance differences between two cements (p < 0.05). The Tukey’s test showed no significant difference only for the 24 and 48 h after light irradiation for both resin cements (p > 0.05). The Relx-Y™ Unicem mean values were significantly higher than Panavia® F 2.0. The degree of conversion means values increasing with the storage time and the filler content showed similar for both resin cements.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".