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Clinical wear of overdenture ball attachments after 1, 3 and 8 years

2011· article· en· W1532463063 on OpenAlexaff
Olivier Fromentin, Claire Lassauzay, Samer Abi Nader, J.S. Feine, Rubens Ferreira de Albuquerque

Bibliographic record

VenueClinical Oral Implants Research · 2011
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsMcGill University
Fundersnot available
KeywordsDentistryMedicineMaterials scienceOrthodonticsBall (mathematics)MathematicsGeometry

Abstract

fetched live from OpenAlex

OBJECTIVES: Implant-supported overdentures have become the treatment of choice in restoring complete edentulism, but the types of attachment to assure durable retention are a subject of debate. Ball attachments were reported as a simple treatment, but wear of components was responsible for a decrease in retention. The aim of this retrospective study was to measure the wear of the ball abutment or patrix after three different periods of clinical wear. MATERIAL AND METHODS: Sixty-nine specimens of three groups of patrix that were in use for a mean of 12.3 months (group A), 39 months (group B) and 95.6 months (group C) were retrieved from 35 patients and measured on a coordinate measuring machine equipped with a touch trigger probe. Ten unused ball abutments were added as a control (group D). The patrix diameters and any deviation from circularity in different axes were measured. RESULTS: The diameters of groups A, B and C were significantly different from that of group D (control). No statistically significant differences were found between diameter and circularity variations between groups B and C. The maximal amount of diameter reduction was limited to approximately 30 μm, and 90% of diameter loss at the equator due to wear was reached in group B. CONCLUSION: One, 3 and 8 years of clinical wear reduced significantly the diameters of the ball abutments tested, and the maximal amount of wear was reached after 3 years of clinical use.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.402
GPT teacher head0.564
Teacher spread0.163 · 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; both teacher heads agree on what is shown here.

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

Citations21
Published2011
Admission routes1
Has abstractyes

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