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Record W3211857599 · doi:10.1115/imece2000-2495

Modelling of Mechanically Regulated Tissue Formation Around Bone-Interfacing Implants

2000· article· en· W3211857599 on OpenAlexaff
Craig A. Simmons, S. A. Meguid, Robert M. Pilliar

Bibliographic record

VenueAdvances in Bioengineering · 2000
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOsseointegrationInterfacingImplantBiomedical engineeringInterlockDentistryMaterials scienceFixation (population genetics)Bone formationReliability (semiconductor)Bone tissueComputer scienceMedicineEngineeringMechanical engineeringSurgeryPhysicsComputer hardware

Abstract

fetched live from OpenAlex

Abstract The clinical success of bone-interfacing orthopaedic and dental implants is dependent on adequate fixation of the implant by mechanical interlock with ingrown bone tissue (i.e., functional osseointegration). The rate and reliability with which osseointegration is achieved are influenced by a number of factors, including the surface geometry of the implant (Thomas and Cook, 1985; Simmons et al., 1999). However, the mechanisms by which implant surface geometry influences initial bone formation remain unresolved. Identifying the factors that allow bone-interfacing implants to osseointegrate more rapidly and reliably should lead to improvements in their use and design.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.225
Teacher spread0.214 · 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 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

Citations1
Published2000
Admission routes1
Has abstractyes

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