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Record W2068824784 · doi:10.1515/bmt.2008.039

Finite element representation of bone substitute remodelling in the jaw bone

2008· article· en· W2068824784 on OpenAlexfundno aff
Tomasz Gedrange, Jens Weingaertner, Volker Hietschold, Christoph Bourauel, Winnie Pradel, Günter Lauer, Peter Proff

Bibliographic record

VenueBiomedizinische Technik/Biomedical Engineering · 2008
Typearticle
Languageen
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsnot available
FundersUniversity of Calgary
KeywordsFinite element methodFixation (population genetics)Bone remodelingRadiographyBiomedical engineeringJaw boneMaterials scienceComputer scienceStructural engineeringMedicineRadiologyEngineeringSurgeryImplant

Abstract

fetched live from OpenAlex

The finite element (FE) method was originally developed on a physical basis for the computation of structure-mechanical problems. Meanwhile, it has been widely applied to medical issues. This study sought a suitable method to build a FE model for remodelling processes in osseous defects supplemented with bone substitute material. For this purpose, the second right premolars were extracted from four pig mandibles (Sus scrofa domesticus) and the extraction alveoli were provided with synthetic bone substitute material. After 70 days, a segmented osteotomy of this area was performed for specimen collection. Radiographs of the specimens were taken in defined planes before and after fixation and embedded with Technovit 9100. Fixation-related shrinkage was quantified from the radiographs using reference lines. Computer tomographic (CT) and microCT images of the fixed and embedded specimens were obtained. From these data, a FE model was built. The construction of a FE model is sufficient to represent bone remodelling after supply of bone substitute material. The use of microCT data permits building a clearly more precise model.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.263
Teacher spread0.240 · 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 designSimulation or modeling
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

Citations14
Published2008
Admission routes1
Has abstractyes

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