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Record W3114554702 · doi:10.46889/jdhor.2020.1204

Multiple Supplemental and Impacted Teeth (Polydent): A Non Syndromic Case Report

2020· article· en· W3114554702 on OpenAlexaff
Louis Z.G. Touyz, Daphna Vermes

Bibliographic record

VenueJournal of Dental Health and Oral Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicdental development and anomalies
Canadian institutionsMcGill University
Fundersnot available
KeywordsDentistryMedicineOrthodontics

Abstract

fetched live from OpenAlex

Many cases of supernumerary teeth are found in congenital syndromes. Most prevalent dental modifications found, are the number of teeth in genetic conditions affecting ectodermal structures including Cleidocranial Dysostosis (CCD), hypohydrotic ectodermal dysplasia, focal dermal hypoplasia, craniofacial dysostosis, and aperts syndrome. The patient's main complaint was of toothache. Clinically there were no macroscopically detectable abnormalities, and he was unaware of any dental problems. His physical and facial appearance showed no deviations from normal, and he chewed, swallowed and spoke without impediment. A complement of permanent human teeth is usually 32, within four quadrants of the mouth; from the center point there are two incisors, one canine, two pre-molars and three molars. Total 4 8 =32 teeth and humans rarely develop more. Presented here is a case with multiple extra supplemental teeth eight in number in his permanent dentition, most of which six were identified radiographically and impacted. This case presented no other identifiable abnormalities in the mouth. The patient's pain derived from one supplemental upper premolar, which was removed. Exodontia other teeth not in function was advised, the patient acknowledged this but failed to return. This unique presentation with supplemental teeth and impactions was deemed to be non-syndromic.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.350

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 studies0.0000.000
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 head0.055
GPT teacher head0.403
Teacher spread0.348 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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