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Record W4409734389

Peripheral Odontogenic Fibroma in a Child.

2025· article· en· W4409734389 on OpenAlexaff
Matheus de Castro Costa, Nayara Nery De Oliveira Cunha, Lísia Aparecida Costa Gonçalves, Noé Vital Ribeiro, Felipe Fornias Sperandio, Sara Ferreira dos Santos Costa, Marina Lara de Carli

Bibliographic record

VenuePubMed · 2025
Typearticle
Languageen
FieldDentistry
TopicOral and Maxillofacial Pathology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsOdontogenicPeripheralMedicineOrthodonticsDentistryPathologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Peripheral odontogenic fibroma (POdF) is a rare and benign mesenchymal odontogenic tumor that stands out as a distinctive entity. It is predominantly found in the gingiva and can present as a diagnostic challenging lesion due to its potential resem- blance to reactive oral lesions. The purpose of this report is to describe a case of a POdF in a 10-year-old child and highlight the importance of recognizing this lesion in the pediatric population. This report also explores the essential diagnostic differentials that clinicians should consider when examining a palpable soft tissue nodule with a firm consistency. Radiographically, well-defined small radiopacities were visible within the lesion, which was indicative of calcified structures. A complete surgical excision was done and histopathological analysis was diagnostic of POdF. The presence of calcifications exhibiting an osteoid/cementoid appearance was confirmed within the lesion. There were no signs of recurrence noted during the 16-month postoperative follow-up period. This case underscores the significance of PodF, which may be included in the differential diagnosis of gingival lesions in pediatric patients.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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
Published2025
Admission routes1
Has abstractyes

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