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An <i>in vitro</i> investigation of the effectiveness of bioactive glass air‐abrasion in the ‘selective’ removal of orthodontic resin adhesive

2008· article· en· W2155523211 on OpenAlexaff
Avijit Banerjee, George Paolinelis, Michal Socker, Fraser McDonald, Timothy F. Watson

Bibliographic record

VenueEuropean Journal Of Oral Sciences · 2008
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsSt. Thomas Hospital
FundersEngineering and Physical Sciences Research Council
KeywordsEnamel paintMaterials scienceScanning electron microscopeAbrasion (mechanical)PolishingAdhesiveProfilometerComposite materialTungsten carbideSurface roughnessDentistryBracketTooth surfaceLayer (electronics)Medicine

Abstract

fetched live from OpenAlex

The process of clinically debonding orthodontic brackets causes histomorphological damage to enamel that needs to be quantified and minimized. This study compared three methods for removing residual resin adhesive following bracket debonding. The surface finish following removal of residual adhesive using a slow-speed eight-bladed tungsten carbide bur (group 1), alumina air-abrasion (group 2), and bioactive-glass air-abrasion (group 3) and following polishing, was examined using scanning electron microscopy imaging of resin replicas. Contact profilometry was used to image surfaces before and after debonding for quantifiable volumetric analysis of enamel damage. Surface scarring was seen on scanning electron micrographs from group 1, a sharp pitted surface was identified in group 2, while group 3 exhibited similar, but subjectively smoother, pits. The surface finish following polishing was similar for groups 2 and 3 but did not completely remove the scarring evident from group 1. Quantifiable enamel lost was as follows: group 1, 0.285 mm(3); group 2, 0.386 mm(3); and group 3, 0.135 mm(3); statistical differences were observed between groups 2 and 3. From these results, bioactive-glass air-abrasion more consistently caused less physical damage to enamel and achieved a clinically smooth surface finish following polishing and is therefore to be recommended for 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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.037
GPT teacher head0.286
Teacher spread0.249 · 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.

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

Citations64
Published2008
Admission routes1
Has abstractyes

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