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Record W4409558878 · doi:10.1002/cnm.70041

Comparative Analysis of Various Cavosurface Margins in Class <scp>II</scp> Restorations Using <scp>3D</scp> Finite Element Method

2025· article· en· W4409558878 on OpenAlex
Zuzanna Apel, Behzad Vafaeian, Joanna Zarzecka, Jenna Wuzinski, Derek B. Apel

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

VenueInternational Journal for Numerical Methods in Biomedical Engineering · 2025
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBevelMaterials scienceFinite element methodAdhesiveUltimate tensile strengthComposite materialShear (geology)Shear stressStructural engineeringLayer (electronics)Engineering

Abstract

fetched live from OpenAlex

The primary aim of these analyses was to evaluate the mechanical characteristics of the restored proximal surface of the lower first molar by comparing four different preparation designs: (a) slot preparation, (b) slot preparation with bevel, (c) slot preparation with bevel and rounded proximal box corners (RPBC), and (d) slot preparation with bevel, rounded proximal box corners, and gingival bevel (GB). The finite element method was utilized to assess various load scenarios applied to slot and bevelled restorations prepared using adhesive restorative materials. The numerical analysis revealed higher tensile stresses by up to 15 MPa when normal traction was applied at the interface between enamel and slot preparations than at the interface between enamel and bevelled preparations. However, the beveled restorations showed increased shear stresses in their thin beveled regions. The results imply a risk of separation for slot restorations. Conversely, incorporating a bevel (with or without RPBC and GB) significantly decreased normal stresses on the restoration edge and shifted it predominantly to compressive stresses. Thus, bevelled restorations may be less prone to debonding at their edges under occlusal loads. However, they may still be susceptible to shear debonding when locally loaded on their thin-beveled regions.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.428
Teacher spread0.390 · 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