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Record W2768644306 · doi:10.1155/2017/5920714

Osseointegration of a 3D Printed Stemmed Titanium Dental Implant: A Pilot Study

2017· article· en· W2768644306 on OpenAlexafffund
James V. Tedesco, Bryan Lee, Alex Lin, Dakota M. Binkley, Kathleen H. Delaney, Jacek M. Kwiecień, Kathryn Grandfield

Bibliographic record

VenueInternational Journal of Dentistry · 2017
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaMcMaster University
KeywordsOsseointegrationImplantBiocompatibilityMaterials scienceTitaniumDentistryBiomedical engineeringScanning electron microscope3d printedMedicineComposite materialSurgery

Abstract

fetched live from OpenAlex

= 4) implants were inserted into the tibial metaphysis of New Zealand white rabbits for 3 and 12 weeks and then retrieved with the surrounding bone, fixed, dehydrated, and embedded into epoxy resin. The implants were analyzed using correlative histology, microcomputed tomography, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The histological presence of multinucleated osteoclasts and cuboidal osteoblasts revealed active bone remodeling in the stemmed implant starting at 3 weeks and by 12 weeks in the conventional implant. Bone-implant contact values indicated that the stemmed implants supported bone growth along the implant from the coronal crest at both 3- and 12-week time periods and showed bone growth into microporosities of the 3D printed surface after 12 weeks. In some cases, new bone formation was noted in between the stems of the device. Conventional implants showed mechanical interlocking but did have indications of stress cracking and bone debris. This study demonstrates the comparable biocompatibility of these 3D printed stemmed implants in rabbits up to 12 weeks.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.287
Teacher spread0.264 · 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 designObservational
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

Citations23
Published2017
Admission routes2
Has abstractyes

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