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Record W1999482285 · doi:10.4012/dmj.28.446

Effect of an internal coating technique on tensile bond strengths of resin cements to zirconia ceramics

2009· article· en· W1999482285 on OpenAlex
Shuzo Kitayama, Toru Nikaido, Rena Maruoka, Lei Zhu, Masaomi Ikeda, Akihiko Watanabe, Richard M. FOXTON, Hiroyuki Miura, Junji Tagami

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDental Materials Journal · 2009
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsSt. Thomas Hospital
FundersTokyo Medical and Dental University
KeywordsMaterials scienceCubic zirconiaComposite materialCeramicSilanizationBond strengthUltimate tensile strengthCoatingDental porcelainSilaneAdhesiveLayer (electronics)

Abstract

fetched live from OpenAlex

This study was conducted to enhance the tensile bond strengths of resin cements to zirconia ceramics. Fifty-six zirconia ceramic specimens (Cercon Base) and twenty-eight silica-based ceramic specimens (GN-1, GN-1 Ceramic Block) were air-abraded using alumina. Thereafter, the zirconia ceramic specimens were divided into two subgroups of 28 each according to the surface pretreatment; no pretreatment (Zr); and the internal coating technique (INT). For INT, the surface of zirconia was coated by fusing silica-based ceramics (Cercon Ceram Kiss). Ceramic surfaces were conditioned with/without a silane coupling agent followed by bonding with one of two resin cements; Panavia F 2.0 (PF) and Superbond C&B (SB). After 24 hours storage in water, the tensile bond strengths were tested (n=7). For both PF and SB, silanization significantly improved the bond strength to GN-1 and INT (p<0.05). The INT coating followed by silanizaton demonstrated enhancement of bonding to zirconia ceramics.

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)0.001
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 score0.015
Threshold uncertainty score0.706

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 head0.007
GPT teacher head0.310
Teacher spread0.303 · 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