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Record W2884537808 · doi:10.1111/cid.12652

A randomized controlled clinical trial assessing initial crestal bone remodeling of implants with a different surface roughness

2018· article· en· W2884537808 on OpenAlexvenueno aff
Maarten Glibert, Carine Matthys, Robert‐Jan Maat, Hugo De Bruyn, Stijn Vervaeke

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2018
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDentistryImplantOsseointegrationMandible (arthropod mouthpart)OrthodonticsRandomized controlled trialRadiographySurgery

Abstract

fetched live from OpenAlex

PURPOSE: The aim of current split-mouth study is to compare crestal bone loss of hybrid with moderately rough implants in patients with a bar-supported mandibular overdenture. MATERIALS AND METHODS: Fully edentulous patients were enrolled for treatment with implant-supported overdentures. Each patient received two implants of which one moderately rough (Sa: 1.3 μm) and one hybrid surface implant (moderately rough implant body [Sa: 1.3 μm] and a minimally rough implant neck [Sa: 0.9 μm]). Beside the difference in implant surface the two implants are identical. After 3 and 12 months, peri-apical radiographs were taken to assess crestal bone levels and a Wilcoxon signed-rank test was used for pairwise comparison. RESULTS: Forty-two implants were placed in 21 patients and no failures occurred after 1 year. An overall mean crestal bone loss of 0.40 mm (SD: 0.76; range: 0-3.93) and 0.35 mm (SD: 0.59; range: 0-2.56) was registered after a mean follow-up of 3.4 and 15.8 months. There was no statistical significant difference in crestal bone loss between the different implant surfaces or between the different time intervals. CONCLUSION: From this randomized controlled trial, it can be concluded that hybrid surface implants may be a viable alternative for implant treatment in the edentulous mandible.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.217
GPT teacher head0.530
Teacher spread0.313 · 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 designRandomized trial
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
Published2018
Admission routes1
Has abstractyes

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