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Record W2994807735 · doi:10.1136/vetreccr-2019-000981

Ependymoma arising from the third ventricle mimicking optic neuritis in a dog

2019· article· en· W2994807735 on OpenAlexaboutno aff
Abbe Crawford, Simon Spiro, K. Christopher Smith, Elsa Beltrán

Bibliographic record

VenueVeterinary Record Case Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsnot available
FundersHorserace Betting Levy BoardPetplan Charitable Trust
KeywordsMedicineOptic chiasmOptic nerveOptic neuritisOptic tractLesionOptic chiasmaEpendymomaOptic neuropathyPathologyOphthalmologyMultiple sclerosis

Abstract

fetched live from OpenAlex

Neurological examination of a 4.5‐year‐old female neutered labrador retriever was consistent with a lesion in the subcortical visual pathway (mainly affecting the left retina or optic nerve, and less likely the optic chiasm or right optic tract). Ophthalmic examination was unremarkable. MRI revealed enlargement of the left optic nerve and optic chiasm. A presumptive diagnosis of immune‐mediated optic neuritis was made and immunosuppressive therapy was commenced. The dog re‐presented 14 days later due to progressive deterioration and generalised seizure activity, and was euthanased. Postmortem examination revealed an anaplastic ependymoma extending from the rostral thalamus along the left optic nerve. Ependymoma can therefore mimic an optic neuropathy, such as immune‐mediated optic neuritis, and should be considered as a 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)0.002
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 score0.014

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 studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0040.002
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 head0.028
GPT teacher head0.284
Teacher spread0.256 · 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
Published2019
Admission routes1
Has abstractyes

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