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Record W4413257304 · doi:10.1007/s12024-025-01061-0

Modified Demirjian’s method for dental age estimation in Kosovar children and adolescents

2025· article· en· W4413257304 on OpenAlexaboutno aff
Jeta Kelmendi, Rizky Merdietio Boedi, Marin Vodanović, Donika Ilijazi Shahiqi, Bleron Azizi, Nikolaos Angelakopoulos

Bibliographic record

VenueForensic Science Medicine and Pathology · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsnot available
FundersUniversity of Bern
KeywordsNormativePopulationMaturity (psychological)MedicineDentistryEstimationDemographyPsychologyEnvironmental healthDevelopmental psychologyLawPolitical scienceSociology

Abstract

fetched live from OpenAlex

AIM: The aim was to provide normative data on dental age estimation in the Kosovar population, to evaluate the relationship between customized maturity scores and the original Demirjian method, and to assess the accuracy of these scores in a sample of Kosovar children and adolescents. MATERIALS AND METHODS: The study population consisted of 1106 digital panoramic radiographs randomly selected from 6- to 16-year-old patients treated at the University Dentistry Clinical Center of Kosovo. Only those images that were diagnostically acceptable, thus showing at least the left mandibular teeth, were included in the study to assess the developmental stage accurately. RESULTS: Dental age estimates derived from the Kosovar normative tables were comparable to those based on maturity scores for the French-Canadian population. In girls aged 7.5-13 years and boys aged 7.5-12 years, dental maturity correlated strongly. However, the French-Canadian model overestimated age significantly compared to the Kosovar sample, where dental maturity started at about 6 years and peaked at 7 years. The Spearman's rho of the relationship between dental ages determined by Demirjian's method and maturity scores obtained from both populations was 0.997 for girls and 0.988 for boys. In conclusion, the present study demonstrates the need for population-specific adaptations of the Demirjian method and proves that modification of the method provides more reliable results when compared to the Kosovar population. The results indicate the possibility of further refinement of the Demirjian method for specific populations in order to improve the applicability and precision of the most commonly used method for age estimation.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.974

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 studies0.0000.029
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 head0.029
GPT teacher head0.328
Teacher spread0.300 · 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 designTheoretical or conceptual
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

Citations1
Published2025
Admission routes1
Has abstractyes

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