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Record W2796358549 · doi:10.3390/met8040247

The Role of a MDP/VBATDT-Primer Composition on Resin Bonding to Zirconia

2018· article· en· W2796358549 on OpenAlexafffund
Anuj Aggarwal, Grace M. De Souza

Bibliographic record

VenueMetals · 2018
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsBond strengthCubic zirconiaMonomerMaterials sciencePhosphoric acidNuclear chemistryChemistryComposite materialAdhesivePolymerMetallurgyCeramic

Abstract

fetched live from OpenAlex

Yttria-tetragonal zirconia polycrystal (Y-TZP) is a difficult substrate to bond to due to the absence of a glass phase and the material’s chemical inertness. This study evaluated the effect of two monomers for metal, MDP (10-methacryloyloxydecyl dihydrogen phosphate) and VBATDT (6-(4-vinylbenzyl-n-propyl)amino-1,3,5-trizaine-2,4-dithiol) on bond strength to Y-TZP. Seven combinations with different concentrations of MDP and VBATDT-monomers (0.0, 0.1, 0.5, or 1.0 wt %) in acetone solution were developed and applied to the surface of Y-TZP slabs, which were bonded to composite resin substrates using a resin cement under standard loading. Non-primed samples were used as controls. Bonded specimens were cut for microtensile testing and tested after either 48 h or 180 days in water storage at room temperature. All samples from control group (no primer) and MV5 group (0% MDP/0.5% VBATDT) debonded spontaneously. Two-way ANOVA showed that the primer had a significant effect (p < 0.001) on bond strength to zirconia, whilst storage time did not (p = 0.203). Tukey HSD (honest significant difference) test indicated that groups with at least 0.5% of each monomer resulted in higher initial bond strength values. Although chemical bonding to zirconia is credited to MDP, a correct balance between MDP and VBATDT may imply in better bond strength results. The minimum concentration of each monomer should not be lower than 0.5 wt %.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.999

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.017
GPT teacher head0.296
Teacher spread0.279 · 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.

Study designBench or experimental
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

Citations7
Published2018
Admission routes2
Has abstractyes

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