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Record W2042890173 · doi:10.4012/dmj.2009-110

Thin resin coating by dual-application of all-in-one adhesives improves dentin bond strength of resin cements for indirect restorations

2010· article· en· W2042890173 on OpenAlexaff
Rena Takahashi, Toru Nikaido, Meu Ariyoshi, Shuzo Kitayama, Alireza Sadr, Richard M. FOXTON, Junji Tagami

Bibliographic record

VenueDental Materials Journal · 2010
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsSt. Thomas Hospital
FundersTokyo Medical and Dental University
KeywordsMaterials scienceAdhesiveBond strengthDentinComposite materialUltimate tensile strengthCoatingDental bondingLayer (electronics)

Abstract

fetched live from OpenAlex

This study was evaluated the tensile bond strength (TBS) of resin cements to bovine dentin resin-coated with all-in-one adhesive systems. Each of the dual-polymerizing resin cements; Link Max, Clearfil Esthetic Cement, Bistite II and Chemiace II were used to bond indirect resin disks to bovine dentin, as control, or coated by single-application or by dual-application of an adhesive system from the same manufacturer; G-Bond, Clearfil Tri-S Bond, Tokuyama Bond Force and Hybrid-Coat (n=10). After 24-hour water storage, TBSs were measured. The fracture pattern and the adhesive interface were observed using an SEM. Dual-application of the adhesive yielded significantly higher TBSs compared to control and single-application groups for all materials (p<0.001). From the limited information of this study, it was concluded that dual-application of all-in-one adhesive systems created a thin coating on dentin, and significantly improved the bond strengths of resin cements.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.796

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 head0.025
GPT teacher head0.305
Teacher spread0.280 · 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 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

Citations28
Published2010
Admission routes1
Has abstractyes

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