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Record W1571951221 · doi:10.21726/rsbo.v8i4.1090

Comparison of MTA Fillapex radiopacity with five root canal sealers

2012· article· en· W1571951221 on OpenAlexaff
Ana Paula Meirelles Vidotto, Rodrigo Sanches Cunha, Eduardo Gregatto Zeferino, Daniel Guimarães Pedro Rocha, Alexandre Sigrist De Martin, Carlos Eduardo da Silveira Bueno

Bibliographic record

VenueRSBO · 2012
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsRadiodensityRoot canalDentistryRoot Canal Filling MaterialsOrthodonticsMedicineSurgeryRadiography

Abstract

fetched live from OpenAlex

Introduction: The endodontic sealer is a filling material whose physicochemical properties are mandatory for the achievement of endodontic therapy final goal. An ideal endodontic sealer should have some properties, including radiopacity. Objective: This study compared MTA Fillapex™ radiopacity with the radiopacity of five others endodontic sealers: Endométhasone-N™, AH Plus™, Acroseal™, Epiphany SE™ and RoekoSeal™. Material and methods: Five cylindrical samples of each sealer were used, constructed with the aid of a matrix. On an occlusal film, a sample of each sealer was placed along with an aluminum stepwedge and five radiographic shots were taken. The radiographic images were digitized and each sample’s gray scales were compared with each shade of the aluminum stepwedge, by using software. Results: The results, in decreasing order of radiopacity, were: AH Plus™ was statistically the most radiopaque sealer (9.4 mm Al), followed by Epiphany SE™ (7.8 mm Al), MTA Fillapex™ (6.5 mm Al), RoekoSeal™ (5.8 mm Al), Endométhasone-N™ (4.5 mm Al), and Acroseal™, the least statistically radiopaque (3.5 mm Al). Conclusion: It can be concluded that MTA Fillapex™ was the third most radiopaque sealer among all tested sealers. Also, MTA Fillapex™ has the radiopacity degree in agreement with ADA specification No. 57 (1983).

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.036
GPT teacher head0.327
Teacher spread0.292 · 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 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

Citations12
Published2012
Admission routes1
Has abstractyes

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