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Record W4393051318 · doi:10.1111/aej.12843

Adhesion and sealing of different universal adhesive systems associated with bulk‐fill resins after using endodontic irrigation solutions: An in vitro study

2024· article· en· W4393051318 on OpenAlexaff
Érika Mayumi Omoto, Anderson Catelan, Paulo Henrique dos Santos, Luciano Tavares Ângelo Cintra, Fernanda de Souza e Silva Ramos, Caio César Pavani, André Luíz Fraga Briso, Ticiane Cestari Fagundes

Bibliographic record

VenueAustralian Endodontic Journal · 2024
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Toronto
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsSodium hypochloriteAdhesiveMolarDentistryDentinMaterials scienceChlorhexidineAdhesionPulp (tooth)Bond strengthSmear layerChemistryComposite materialMedicine

Abstract

fetched live from OpenAlex

This study aimed to evaluate the interface of universal adhesive (UA) with bulk-fill resin (BF) and dentin, after endodontic irrigation. The pulp chamber of 96 molars was irrigated with chlorhexidine 2% (CHX) or sodium hypochlorite 5.25% (NaOCl) and restored according to three restorative protocols. Microtensile bond strength (μTBS) and nanoleakage tests were performed after 24 h of thermocycling. Kruskal Wallis, Mann-Whitney and Wilcoxon were performed (p < 0.05). Comparing restorative systems, a difference was found only when irrigated with CHX after 24 h. CHX provided higher μTBS than NaOCl after 24 h for two restorative protocols; after thermocycling, NaOCl provided the greatest μTBS than CHX for one group. Decreased μTBS was observed for all restorative systems when CHX was used after thermocycling. NaOCl demonstrated the highest nanoleakage. The composition of UA influenced the immediate adhesion and sealing to BF when CHX was used; ageing has a deteriorating effect on adhesion and sealing for all restorative systems.

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)0.000
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 score0.771
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.043
GPT teacher head0.290
Teacher spread0.247 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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