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Record W2038453199 · doi:10.4012/dmj.25.261

Effect of Curing Method and Storage Condition on Fluoride Ion Release from a Fluoride-releasing Resin Cement

2006· article· en· W2038453199 on OpenAlexaff
Akira Yoda, Toru Nikaido, Masaomi Ikeda, H Sonoda, Richard M. FOXTON, Junji Tagami

Bibliographic record

VenueDental Materials Journal · 2006
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsSt. Thomas Hospital
FundersTokyo Medical and Dental University
KeywordsMaterials scienceFluorideCuring (chemistry)CementComposite materialIonInorganic chemistryOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate fluoride ion release from a resin-modified glass ionomer cement (Fuji IILC improved, FLC) and a fluoridated resin cement (Panavia F, PF) following different curing methods and storage conditions. The specimens, which were either light-cured (LC) or chemical-cured (CC), were stored in either distilled water (DW) or demineralizing solution (DS; pH 4.5) for 1, 3, 7, 15, 30, 60, and 90 days. Fluoride ion release was measured using a fluoride ion-specific electrode. Data (n = 5) were statistically analyzed using one- and three-way ANOVA (p = 0.05). A "burst effect" was observed in the first week from both materials. However, fluoride ion release from FLC was seven times higher than that from PF. Storage in demineralizing solution accelerated the amount of fluoride release from both materials. In addition, LC yielded a lower amount of fluoride ion release from both materials, as compared to CC. It was concluded that both curing mode and storage medium influenced the amount of fluoride release from the tested materials.

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 score0.048
Threshold uncertainty score0.877

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)0.0010.000

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 head0.007
GPT teacher head0.285
Teacher spread0.278 · 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

Citations30
Published2006
Admission routes1
Has abstractyes

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