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Record W2114155103 · doi:10.1002/jbm.b.31624

Initial evaluation of bone ingrowth into a novel porous titanium coating

2010· article· en· W2114155103 on OpenAlexaff
Rima Wazen, Louis‐Philippe Lefebvre, Éric Baril, Antonio Nanci

Bibliographic record

VenueJournal of Biomedical Materials Research Part B Applied Biomaterials · 2010
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMaterials scienceOsseointegrationPorosityCoatingTitaniumBiomedical engineeringComposite materialImplantInterlockingTibiaMetallurgySurgery

Abstract

fetched live from OpenAlex

Porous metals (sintered beads and meshes) have been used for many years for different orthopedic applications. Metal foams have been recently developed. These foams have the advantage of being more porous than the traditional coatings. Their high porosity provides more space for bone ingrowth and mechanical interlocking and presents more surface for implant-bone contact. The objective of this study was to evaluate in vivo bone ingrowth into Ti implants covered with a novel Ti foam coating. This foam contains 50% in volume of interconnected pores and a higher surface area compared to dense Ti. Both coated implants and dense Ti controls were placed transcortically in the rat tibia. The animals were sacrificed at 2 weeks after implantation, and the amount of bone in the implants was determined using backscattered electron imaging and X-ray microtomography. Already at this time interval, the pores within the Ti foam showed 97.7% bone filling, and the bone-implant contact area was significantly increased compared to dense Ti controls. These initial results indicate that this novel Ti foam is biocompatible, has the capacity to sustain bone formation, and can potentially improve osseointegration.

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)0.020
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.055
GPT teacher head0.353
Teacher spread0.298 · 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

Citations62
Published2010
Admission routes1
Has abstractyes

Explore more

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