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Finite Element Analysis of a New Custom Made Orthotropic Post Material for Dental Applications

2008· article· en· W1996605475 on OpenAlexaff
Manoj Khanal, Ying Zheng, Zengtao Chen

Bibliographic record

VenueAdvanced materials research · 2008
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsCementMaterials scienceFinite element methodOrthotropic materialComposite materialDentinStress (linguistics)Elastic modulusModulusStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Effects of cement properties on stress distributions at the dentin-cement-post interfaces have been studied using 3D explicit finite element simulations. The mastication and horizontal loadings are simulated with titanium and glass fiber posts. Different type of cements (moduli 2,8,18 and 22 GPa) is considered to study the interface stresses. The interface stresses are evaluated at dentin-cement-post interfaces and along the surface of the post and cement. The element deletion technique from finite element analysis has been used to predict the cement failure. The simulation results suggest that the cement with similar modulus as dentin is preferable to avoid the stress concentration at the dentin-cement interface. The types of cement do not affect the failure initiation location on the cement. Under the simulated conditions, the failure initiation is located at 1.7 to 2.2 mm from the post apex.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.040
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.390
Teacher spread0.334 · 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.

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

Citations0
Published2008
Admission routes1
Has abstractyes

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