Evaluation of the micromorphology of the hybrid layer in caries-affected dentin: a systematic review
Bibliographic record
Abstract
Introduction: Conventional restorative procedures demand the inclusion of caries-affected dentin (CAD) in tooth preparation.Developments in adhesive dentistry preclude the removal of the affected layer by achieving bonding to it.This systematic review was undertaken to evaluate the micromorphology that was seen in a hybrid layer formed within CAD.Objectives: The aim of this review was to evaluate the micromorphology of the hybrid layer in caries-affected dentin.Material and methods: PubMed and Google Scholar databases were searched according to the inclusion and exclusion criteria from September 2010 to August 2020.References from articles were manually searched.Full-text articles available in the English language were chosen.Data extraction and quality assessment of selected articles were independently performed by two authors and a third author was consulted when needed.The risk of bias was assessed using the MINORS checklist.Data were entered in appropriate tables for assessment of obtained results.Results: Out of the 328 search results, 325 were excluded and 3 studies were selected for inclusion in the present review.This systematic review favored sound dentin (SoD) over CAD.Morphological and chemical characteristics strongly influence the response of CAD in bonding which, regardless of the type of adhesives, demonstrates lower strength and durability than sound dentin.Conclusions: Based on the studies included in the review, it can be concluded that despite the improvement in adhesion technology over recent decades, CAD bonding needs to be further understood and improved.
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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 | 0.014 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".