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Record W2162064751 · doi:10.2341/14-240-l

Microshear Bond Strength of Resin Cements to Lithium Disilicate Substrates as a Function of Surface Preparation

2015· article· en· W2162064751 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOperative Dentistry · 2015
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsnot available
FundersBayer CanadaUniversity of Minnesota
KeywordsSilaneMaterials scienceAdhesiveComposite materialBond strengthHydrofluoric acidCementCeramicMetallurgy

Abstract

fetched live from OpenAlex

OBJECTIVES: To investigate the effect of hydrofluoric acid (HF) etching, silane solution, and adhesive system application on the microshear bond strength (μSBS) of lithium disilicate glass-ceramic (LD) to three resin cements. MATERIALS AND METHODS: Circular bonding areas were delimited on the lithium disilicate surfaces using a perforated adhesive tape. Specimens were assigned to 18 subgroups (n=12) according to surface treatment: NT = no treatment; HF = 4.8% HF for 20 seconds; silane solution: (1) no silane; (2) Monobond Plus, a silane/10-methacryloyloxydecyl dihydrogen phosphate solution for 60 seconds; (3) Monobond Plus+ExciTE F DSC, a dual-cure adhesive; and resin cement: (1) Variolink II, a bisphenol A diglycidyl ether dimethacrylate (bis-GMA)-based, hand-mixed, dual-cure resin cement; (2) Multilink Automix, a bis-GMA-based, auto-mixed, dual-cure resin cement; (3) RelyX Unicem 2, a self-adhesive, auto-mixed, dual-cure resin cement. Tygon tubes (Ø=0.8 mm) were used as cylinder matrices for resin cement application. After 24 hours of water storage, the specimens were submitted to the μSBS test. Mode of failure was evaluated under an optical microscope and classified as adhesive, mixed, cohesive in resin cement, or cohesive in ceramic. Data were statistically analyzed with three-way analysis of variance and Dunnett test (p<0.05). RESULTS: When means were pooled for the factor surface treatment, HF resulted in a significantly higher μSBS than did NT (p<0.0001). Regarding the use of a silane solution, the mean μSBS values obtained with Monobond Plus and Monobond Plus+ExciTE F DSC were not significantly different but were higher than those obtained with no silane (p<0.001). Considering the factor resin cement, Variolink II resulted in a significantly higher mean μSBS than did RelyX Unicem 2 (p<0.03). The mean μSBS for Multilink Automix was not significantly different from those of Variolink II and RelyX Unicem 2. According to Dunnett post hoc test (p<0.05), there was no significant difference in μSBS between the different resin cements for HF-etched and silanized (with or without adhesive application) LD surfaces. CONCLUSION: LD may benefit from pretreatment of the inner surface with HF and silanization, regardless of the resin cement used.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.633

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)0.0000.000

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 head0.033
GPT teacher head0.342
Teacher spread0.309 · 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