MétaCan
Menu
Back to cohort
Record W2287827338 · doi:10.4103/0975-1475.176956

Dental age assessment among Tunisian children using the Demirjian method

2016· article· en· W2287827338 on OpenAlexaboutno aff
Abir Aissaoui, Nidhal Haj Salem, Meryam Mougou, Fethi Maatouk, Ali Chadly

Bibliographic record

VenueJournal of Forensic Dental Sciences · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePopulationAge groupsDentistryDemographyEnvironmental health

Abstract

fetched live from OpenAlex

CONTEXT: Since Demirjian system of estimating dental maturity was first described, many researchers from different countries have tested its accuracy among diverse populations. Some of these studies have pointed out a need to determine population-specific standards. AIM: The aim of this study is to evaluate the suitability of the Demirjian's method for dental age assessment in Tunisian children. MATERIALS AND METHODS: This is a prospective study previously approved by the Research Ethics Local Committee of the University Hospital Fattouma Bourguiba of Monastir (Tunisia). Panoramic radiographs of 280 healthy Tunisian children of age 2.8-16.5 years were examined with Demirjian method and scored by three trained observers. STATISTICAL ANALYSIS USED: Dental age was compared to chronological age by using the analysis of variance (ANOVA) test. Cohen's Kappa test was performed to calculate the intra- and inter-examiner agreements. RESULTS: Underestimation was seen in children aged between 9 and 16 years and the range of accuracy varied from -0.02 to 3 years. The advancement in dental age as determined by Demirjian system when compared to chronological age ranged from 0.3 to 1.32 year for young males and from 0.26 to 1.37 year for young females (age ranged from 3 to 8 years). CONCLUSIONS: The standards provided by Demirjian for French-Canadian children may not be suitable for Tunisian children. Each population of children may need their own specific standard for an accurate estimation of chronological age.

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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.033
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 head0.041
GPT teacher head0.338
Teacher spread0.297 · 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

Citations37
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Forensic Dental SciencesSame topicForensic Anthropology and Bioarchaeology StudiesFrench-language works237,207