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Record W3194396227 · doi:10.1159/000518806

Carotid Cavernous Sinus Fistula with Contralateral Feed Not Diagnosed by Virtual Assessment or by Non-Invasive Vascular Imaging

2021· article· en· W3194396227 on OpenAlexaff
Edsel Ing, Felix Tyndel, Joyce Tang, Thomas R. Marotta

Bibliographic record

VenueCase Reports in Ophthalmology · 2021
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations Diagnosis and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineDigital subtraction angiographySuperior ophthalmic veinRadiologyCavernous sinusFistulaCarotid-Cavernous Sinus FistulaInferior petrosal sinusAngiographyCarotid-cavernous fistula

Abstract

fetched live from OpenAlex

A 67-year-old woman had delayed initial diagnosis of her right low flow carotid cavernous fistula (CCF) during the coronavirus disease (COVID-19) pandemic due to difficulty detecting ocular signs via online virtual examinations. Her right eye conjunctival erythema and proptosis with medial rectus enlargement on computed tomography scan was initially misdiagnosed as euthyroid thyroid-associated orbitopathy without lid retraction. She developed vision loss, and increasing episcleral venous congestion and CCF was suspected. Computed tomographic angiography did not show an obvious fistula. Digital subtraction angiography revealed the right-sided low flow CCF, which was fed from vessels from the contralateral side.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.205
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.283
Teacher spread0.272 · 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 teacher head, not a consensus.

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
Published2021
Admission routes1
Has abstractyes

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