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Tissue Characteristics at Microthreaded Implants: An Experimental Study in Dogs

2006· article· en· W2165853034 on OpenAlexvenueno aff
Ingemar Abrahamsson, Tord Berglundh

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2006
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsOsseointegrationDentistryImplantBeagleAbutmentMandible (arthropod mouthpart)MedicineRadiographyOrthodonticsSurgeryBiology

Abstract

fetched live from OpenAlex

PURPOSE: The aim of the present study was to analyze bone tissue reactions at implants with and without a microthread configuration. MATERIALS AND METHODS: In six beagle dogs, one test and two control implants were installed in one side of the mandible. While both implant types had a similar dimension and surface roughness, the test implants were designed with a microthread configuration in the marginal portion. Abutment connection was performed after 3 months. Another 3 months later, fixed partial dentures (FPDs) were cemented to the maxillary canine and premolars and FPDs were connected to the implants in the mandible. Ten months later, the animals were sacrificed and biopsies from each implant region were processed for histological analysis. Radiographs were obtained at implant placement after FPD connection and at the termination of the experiment. RESULTS: The radiographic examination revealed that the marginal bone level was well preserved at both test and control implants during the entire 16-month period. The degree of bone-implant contact within the marginal portion of the implants was significantly higher at the test (microthread) implants (81.8%) than at the control implants (72.8%). CONCLUSIONS: It was suggested that the microthread configuration offered improved conditions for 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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.136
GPT teacher head0.498
Teacher spread0.362 · 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 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

Citations114
Published2006
Admission routes1
Has abstractyes

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