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Record W2899160389 · doi:10.2319/011518-46.1

A novel technique for measurement of orthodontic mini-implant stability using the Osstell ISQ device

2018· article· en· W2899160389 on OpenAlexaff
Yara K. Hosein, S. Jeffrey Dixon, Amin S. Rizkalla, Ali Tassi

Bibliographic record

VenueThe Angle Orthodontist · 2018
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsWestern University
Fundersnot available
KeywordsImplant stability quotientResonance frequency analysisReproducibilityRepeatabilityImplantDentistryInitial stabilityOsseointegrationMaterials scienceBiomedical engineeringMedicineMathematicsSurgery

Abstract

fetched live from OpenAlex

OBJECTIVES: To develop and validate a method for application of the Osstell ISQ device in the assessment of mini-implant stability. MATERIALS AND METHODS: An adaptor was developed for attachment of Osstell's SmartPeg onto a variety of orthodontic mini-implants. For validation of the adaptor, Benefit mini-implants were inserted into bone blocks that mimicked different stability conditions. The Osstell device was used to assess mini-implant stability with the adaptor (test measurement) and conventional SmartPeg attachment (gold-standard measurement). Implant stability quotient (ISQ) values were assessed for agreement, repeatability, and reproducibility. RESULTS: Strong positive correlations were found between ISQ values obtained using the novel adaptor and the conventional attachment. Repeatability and reproducibility of ISQ values with the adaptor were similar to those obtained with the conventional attachment. CONCLUSIONS: A method was developed and validated to assess the stability of orthodontic mini-implants using the Osstell system. The novel mini-implant adaptor provided repeatable and reproducible measurements of mini-implant stability, which agreed with those obtained using a conventional SmartPeg attachment. This adaptor permits noninvasive stability assessment of various designs of mini-implants, most of which are incompatible with the conventional SmartPeg attachment.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.476
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.144
GPT teacher head0.339
Teacher spread0.196 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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