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Record W2228038314 · doi:10.4103/0972-0707.168833

Effect of silorane-based adhesive system on bond strength between composite and dentin substrate

2015· article· en· W2228038314 on OpenAlexaff
Jefferson Ricardo Pereira, LindomarCorrêa Júnior, Mauro de Souza Almeida, AccácioLins do Valle, HeitorMarques Honório, Hugo Alberto Vidotti, Grace M. De Souza

Bibliographic record

VenueJournal of Conservative Dentistry · 2015
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComposite numberMaterials scienceAdhesiveDentinSubstrate (aquarium)Bond strengthComposite material

Abstract

fetched live from OpenAlex

CONTEXT: The complexities of the oral environment, the dentin substrate, and the different bond and composite resin systems represent a challenge to the maintenance of reasonable bond between the composite resin and the tooth structure. AIMS: To evaluate the effect of the adhesive system on bond strength between silorane-based composite resin and dentin. MATERIALS AND METHODS: Fourteen human molars extracted were selected and vertically cut into 3 dentin fragments, randomly divided among the experimental groups and restored with Z250 and P90 composite resin using different adhesive protocols (Adper Single Bond 2, Silorano primer, Adper SE Plus, and Scotchbond Multiuse). Two composite resin cylinders were built up on each dentin surface (n = 10) and subjected to a micro-shear bond strength test. STATISTICAL ANALYSIS USED: Kruskal-Wallis one-way analysis of variance and Tukey test (P = 0.05). RESULTS: According to the results, Kruskal-Wallis test evidenced at least one statistical significant difference (P = 0.001). The Tukey test showed statistically significant differences among the group (P < 0.05). Group PSM8 (P90 + SM) showed statically significant higher results when compared with groups PSP4 (P90 + SP), PSB2 (P90 + SB), and ZSE5 (Z250 + SE). CONCLUSION: The results evidenced that the monomer of the adhesive system has an effect on bond strength between the composite resin and dentin.

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 score0.432
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.031
GPT teacher head0.305
Teacher spread0.274 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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