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Record W2994626961

Peripheral cranial neuropathies consistent with cavernous sinus syndrome caused by extracranial nasopharyngeal lymphoma in a cat.

2019· article· en· W2994626961 on OpenAlexaff
Stephanie Osinchuk, Danielle Zwueste, Bruce H Grahn

Bibliographic record

VenuePubMed · 2019
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Surgical Oncology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineCavernous sinusCranial nervesWeaknessDifferential diagnosisDysphagiaSinus (botany)Magnetic resonance imagingAnatomyRadiologyPathology
DOInot available

Abstract

fetched live from OpenAlex

Cavernous sinus syndrome is a unique constellation of cranial nerve deficits occurring typically as a result of pathologic infiltration of the cavernous sinus, which is located in the lateral sellar compartment of the calvarium. This case report describes a polyneuropathy consistent with cavernous sinus syndrome as a result of a lesion outside of the cavernous sinus. The cat was presented with right internal and external ophthalmoplegia, loss of right corneal sensation, inspiratory stridor, dysphagia, dysphonia, tongue weakness, and weight loss. Magnetic resonance imaging identified a large nasopharyngeal mass along the base of, but without extension into, the calvarium. The histologic diagnosis was nasopharyngeal lymphoma. Focal extracranial masses should be considered as differential diagnoses for multiple cranial nerve deficits, including the constellation of clinical signs recognized as cavernous sinus syndrome.

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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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