Invitro Comparison of Marginal Microleakage of Three Restoration Materials in Cl V Cavities Prepared by Er:YAG in Primary Teeth
Bibliographic record
Abstract
Introduction: Recently, such alternative methods for tooth preparation as laser irradiation have been studied increasingly, though limited numbers of studies have been conducted in regard with primary teeth. Microleakage involves one of the prominent criteria in evaluating success of adhesive restorative materials. Therefore, the objective of this in vitro study was to compare marginal microleakage of three restorative materials in cl V cavities prepared by Er:YAG laser in primary teeth. Methods: Forty five primary canine teeth were randomly divided in 3 groups. Class V cavities were prepared via Er:YAG laser on buccal surface. The groups 1,2,3 were restored according to the manufacturer's instructions with resin-modified glass ionomer, composite resin and compomer respectively. Then all specimens were polished, thermocycled, and immersed in 2% methylene blue solution and sectioned buccolingually. The specimens were assessed under a stereomicroscope(X20). It should be noted that microleakage assessment was performed by two evaluators who were cognizant of micro leakage scoring (0 to 4). Moreover, the study data were analyzed by applying Exact-test. Results: The study results revealed no significant difference between microleakage of three groups (P-value =0.422) Conclusion: These three restorative materials(resin-modified glass ionomer, composite resin, compomer) were proved to be proper for restoring cl V cavities prepared by Er:YAG laser in primary teeth.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".