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Record W2038583381 · doi:10.4012/dmj.27.187

Dentin Bond Strengths of Three Adhesive/Composite Core Systems using Different Curing Units

2008· article· en· W2038583381 on OpenAlex
Meu Ariyoshi, Toru Nikaido, Ayako Okada, Richard M. FOXTON, 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 · 2008
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsSt. Thomas Hospital
FundersJapan Society for the Promotion of ScienceTokyo Medical and Dental University
KeywordsMaterials scienceComposite materialDentinAdhesiveBond strengthCuring (chemistry)Composite numberUltimate tensile strengthCrossheadFlexural strengthLayer (electronics)

Abstract

fetched live from OpenAlex

This study evaluated the tensile bond strengths of three adhesive/composite core materials to bovine dentin using three different curing units. Bovine dentin surfaces were ground with 600-grit SiC paper. Bonding area was demarcated with a vinyl tape (4-mm-diameter hole). Three adhesive/composite core systems--S6054 (experimental), UniFil Core, and Clearfil DC Core Automix--were used with three curing units--Curing Light XL3000 (quartz-tungsten-halogen), Hyper Lightel (high-power quartz-tungsten-halogen), and LEDemetronl (blue light-emitting diode)--according to manufacturers' instructions. After 24 hours of storage in water at 37 degrees C, tensile bond strengths were measured at a crosshead speed of 2 mm/min. Results were statistically analyzed with one-way ANOVA and Tukey's HSD test (p < 0.05). Highest tensile bond strength was obtained using Clearfil DC Core Automix with Hyper Lightel.

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 categoriesMeta-epidemiology (narrow)
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 score0.184
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.287
Teacher spread0.226 · 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