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Record W2725869609 · doi:10.2319/010417-12.1

Diagnostic reliability of mandibular second molar maturation in the identification of the mandibular growth peak: A longitudinal study

2017· article· en· W2725869609 on OpenAlexfundno aff
Giuseppe Perinetti, Riccardo Sossi, Jasmina Primožič, Gaetano Ierardo, Luca Contardo

Bibliographic record

VenueThe Angle Orthodontist · 2017
Typearticle
Languageen
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsnot available
FundersFaculty of Dentistry, University of TorontoUniversity of TorontoUniversity of the Pacific
KeywordsMandibular molarMolarMandible (arthropod mouthpart)DentistryMedicineOrthodonticsMandibular first molarMandibular second molarBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the diagnostic reliability of mandibular second molar maturation in assessing the mandibular growth peak using a longitudinal design. MATERIALS AND METHODS: From the files of the Burlington and Oregon growth studies, 40 subjects (20 from each collection, 20 males and 20 females) with at least seven annual lateral cephalograms taken from 9 to 16 years were included. Mandibular second molar maturation was assessed according to Demirjian et al., and mandibular growth was defined as annual increments of Co-Gn distance. A full diagnostic reliability analysis (including positive likelihood ratio) was performed to establish the diagnostic reliability of dental stages E, F, and (pooled) GH in identifying the imminent mandibular growth peak. RESULTS: None of the dental maturation stages reliably identified the mandibular growth peak with greatest overall mean accuracy and positive likelihood ratio of 0.77 (stage F) and 2.7 (stage E), respectively. CONCLUSIONS: Use of the mandibular second molar maturation is not recommended for planning treatment requiring identification of the mandibular growth peak.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.290
Teacher spread0.269 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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