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Record W2185983815

Influence of composite inlay/onlay thickness on hardening of dual-cured resin cements.

2000· article· en· W2185983815 on OpenAlexaff
Omar El‐Mowafy, M H Rubo

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInlayKnoop hardness testMaterials scienceComposite materialComposite numberCuring (chemistry)VarnishHardening (computing)CrystallinityHardnessIndentation hardnessMicrostructure
DOInot available

Abstract

fetched live from OpenAlex

This investigation evaluated the effect of resin composite inlay/onlay thickness on the hardness of a group of eight dual-cure resin-based cements. Fourteen disc specimens measuring 6 mm in diameter and 2.5 mm thick were prepared from each of eight dual-cure cements: Adherence, Choice, Duolink, Enforce, Lute-It, Nexus, Resinomer and Variolink. Two specimens from each material were directly light-cured while the remainder of the specimens were light-cured through resin composite spacers varying in thickness from 1 mm to 6 mm. Curing through the spacers always resulted in a decrease in the Knoop hardness number. For some cements, hardness values were reduced by 50% or more when the resin composite spacer thickness was 4 mm or greater even when measurements were made one week after dual-curing. Low hardness values indicate the presence of a weak chemical-curing mechanism that may compromise cement quality in areas of the cavity not readily accessible to the curing light.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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)0.0020.000

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 head0.017
GPT teacher head0.244
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), 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

Citations99
Published2000
Admission routes1
Has abstractyes

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