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Record W2302157823

Microleakage evaluation of class V restorations with conventional and resin-modified glass ionomer cements.

2014· article· en· W2302157823 on OpenAlexaff
Danielson Guedes Pontes, Manoel Valcácio Guedes-Neto, Maria Fernanda Costa Cabral, Flávia Cohen‐Carneiro

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsGlass ionomer cementDentistryMaterials scienceAcrylic resinNuclear chemistryChemistryComposite materialMedicine
DOInot available

Abstract

fetched live from OpenAlex

The aim of this study was to evaluate in vitro the marginal microleakage of conventional Glass Ionomer Cements (GIC) and Resin Modified Glass Ionomer Cements (RMGIC). The tested materials were grouped as follows: GIC category - G1 (Vidrion R - SSWhite); G2 (Vitro Fill - DFL); G3 (Vitro Molar - DFL); G4 (Bioglass R - Biodinâmica); and G5 (Ketac Fill - 3M/ESPE); and RMGIC category - G6 (Vitremer - 3M/ESPE); G7 (Vitro Fill LC - DFL); and G8 (Resiglass - Biodinâmica). Therefore, 80 class V cavities (2.0X2.0 mm) were prepared in bovine incisors, either in the buccal face. The samples were randomly divided into 8 groups and restored using each material tested according to the manufacturer. The root apices were then sealed with acrylic resin. The teeth were stored for 24 h in 100% humidity at 37°C. After storage, the specimens were polished with extra-slim burs and silicon disc (Soft-lex - 3M/ESPE), then were isolated with cosmetic nail polish up to 1 mm around the restoration. Then, the samples were immersed in 50% AgNO3 solution for 12 h and in a developing solution for 30 min. They were rinsed and buccal-lingual sectioned. The evaluation of the microleakage followed scores from 0 to 3. The Kruskal-Wallis test and Dunn method test were applied (a=0.05). The results showed that there was no difference between the enamel and dentin margins. However, GIC materials presented more microleakage than RMGIC.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.726
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.263
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2014
Admission routes1
Has abstractyes

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