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Record W3210471688 · doi:10.1111/aej.12583

Evaluation of the outcome of apexogenesis in traumatised anterior and carious posterior teeth using mineral trioxide aggregate: a 5‐year retrospective study

2021· article· en· W3210471688 on OpenAlexaff
Shima Mousivand, Mahshid Sheikhnezami, Saeed Moradi, Niloufar Koohestanian, Hamid Jafarzadeh

Bibliographic record

VenueAustralian Endodontic Journal · 2021
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsUniversity of TorontoMcGill University
FundersMashhad University of Medical Sciences
KeywordsMineral trioxide aggregateDentistryAnterior teethMedicinePosterior teethPulpotomyRetrospective cohort studyExact testCrown (dentistry)OrthodonticsMolarSurgery

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate the outcome of apexogenesis with mineral trioxide aggregate (MTA) in traumatised anterior and carious posterior teeth over 5 years. A comprehensive chart review was performed to obtain a retrospective of sequential previously completed cases with recalls. Clinical and radiographic data were collected for 97 vital immature teeth (40 traumatised anterior and 57 carious posterior teeth) pulpotomised (partial or full pulpotomy) using MTA with an average follow-up time of 5 years. Chi-squared test and Fisher's exact test were implemented to analyse data. The success rate in anterior teeth and posterior teeth was 82.5% and 96.4% respectively. Crown discolouration was observed in 25 (62.5%) anterior teeth. There was a significant difference between the number of successful and unsuccessful cases (P < 0.05) and there was no correlation between type of treatment and success/failure (P > 0.05). The success rate of apexogenesis using MTA in immature teeth was relatively high.

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)0.001
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 score0.024
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.084
GPT teacher head0.358
Teacher spread0.274 · 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

Citations11
Published2021
Admission routes1
Has abstractyes

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