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Record W2886115088 · doi:10.1111/eve.12978

Sclerosing odontogenic carcinoma in the mandible of a horse

2018· article· en· W2886115088 on OpenAlexaff
Fiona Oliver, P.G. Kelly, S. Sharpe, Ashraf Ayoub, Janet C. Patterson‐Kane, Patrick J. Pollock

Bibliographic record

VenueEquine Veterinary Education · 2018
Typearticle
Languageen
FieldDentistry
TopicOral and Maxillofacial Pathology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineHistopathologyHorseMandible (arthropod mouthpart)RadiographyCarcinomaOdontogenicMandibular NeoplasmsPathologyAnatomyRadiologyMaxilla

Abstract

fetched live from OpenAlex

Summary A 15‐year‐old Cob mare was presented for investigation of a mandibular mass. Radiography identified an oval‐shaped mass occupying the intramandibular space, with a heterogeneous osseous opacity throughout the left hemimandible. Histopathology combined with immunohistochemistry was consistent with a diagnosis of sclerosing odontogenic carcinoma, which to date has only been described, rarely, in human patients. The mass was removed using a mandibular‐sparing surgical technique allowing preservation of the dental arcade. Follow‐up 5 years after surgery confirmed no signs of regrowth. This case report describes the successful treatment of a previously unreported mandibular neoplasm in the horse.

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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.344
Teacher spread0.282 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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