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Record W2546229377 · doi:10.3390/dj4040037

Degree of Conversion and Oxygen-Inhibited Layer Effect of Three Dental Adhesives

2016· article· en· W2546229377 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.

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

Bibliographic record

VenueDentistry Journal · 2016
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAdhesiveMaterials scienceFourier transform infrared spectroscopyOxygenComposite materialLayer (electronics)Curing (chemistry)Nuclear chemistryChemical engineeringChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

This study investigated the effect of the oxygen-inhibited layer on the degree of conversion (DC) of three dental adhesives, comparing two different protocols. Quartz-tungsten-halogen (QTH) light curing and light-emitting diode (LED) were used to cure three adhesives: OptiBond All in One (OAIO), Adper Easy Bond (AEB) and ExciteF (EXF). The DC was calculated utilizing Fourier Transform infrared spectroscopy (FTIR) (n = 12). The two protocols used were as follows: (i) prevent the oxygen-inhibited layer using a Mylar plastic strip pushed onto each bonding adhesive; and (ii) polymerize samples without a plastic strip. The data was analyzed statistically by a three-way ANOVA, and Tukey Test (a = 0.05). The presence of an oxygen-inhibited layer reduced the DC of the adhesives by 64% for EXF, 46% for AEB and 32% for OAIO. This study suggests that there are differences among the oxygen-inhibited layers present for the adhesives tested.

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 score0.227
Threshold uncertainty score0.801

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)0.0010.000

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 head0.023
GPT teacher head0.272
Teacher spread0.248 · 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