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Record W2160981571 · doi:10.1259/dmfr.20110162

Intraosseous mucoepidermoid carcinoma: a review of the diagnostic imaging features of four jaw cases

2013· review· en· W2160981571 on OpenAlexaffabout
Ka Ching Chan, Michael J. Pharoah, L Lee, Ilan Weinreb, Bayardo Perez‐Ordoñez

Bibliographic record

VenueDentomaxillofacial Radiology · 2013
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsToronto General HospitalUniversity Health NetworkPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineMucoepidermoid carcinomaRadiologyBiopsyPerforationSoft tissueAdamantinomaDifferential diagnosisPathologyDentistryCarcinomaMaxillaMaterials scienceAmeloblastoma

Abstract

fetched live from OpenAlex

The purpose of this case series is to present the common features of intraosseous mucoepidermoid carcinoma (IMC) of the jaws in plain film and CT imaging. Two oral and maxillofacial radiologists reviewed and characterized the common features of four biopsy-proven cases of IMC in the jaws in plain film and CT imaging obtained from the files of the Department of Oral Radiology, Faculty of Dentistry, University of Toronto, Toronto, Canada. The common features are a well-defined sclerotic periphery, the presence of internal amorphous sclerotic bone and numerous small loculations, lack of septae bordering many of the loculations, and expansion and perforation of the outer cortical plate with extension into surrounding soft tissue. Other characteristics include tooth displacement and root resorption. The four cases of IMC reviewed have common imaging characteristics. All cases share some diagnostic imaging features with other multilocular-appearing entities of the jaws. However, the presence of amorphous sclerotic bone and malignant characteristics can be useful in the differential diagnosis.

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)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.043
GPT teacher head0.333
Teacher spread0.291 · 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
GenreReview

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

Citations33
Published2013
Admission routes2
Has abstractyes

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