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Record W2063305464 · doi:10.1097/wno.0000000000000095

Optic Chiasm Involvement on MRI With Ethambutol-Induced Bitemporal Hemianopia

2014· article· en· W2063305464 on OpenAlexaff
V B Osaguona, James Sharpe, Samira A. Awaji, Richard Farb, Arun Sundaram

Bibliographic record

VenueJournal of Neuro-Ophthalmology · 2014
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Ocular Toxicity
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsOptic chiasmEthambutolVisual fieldMagnetic resonance imagingHemianopsiaOptic neuropathyNeuroimagingMedicineOptic nerveOphthalmologyRadiologyPathologyPsychiatry

Abstract

fetched live from OpenAlex

While ethambutol optic neuropathy usually causes central or cecocentral scotomas, bitemporal visual field defects also have been reported. The pathogenesis of the bitemporal hemianopia has not been established. This article describes magnetic resonance imaging abnormalities involving the optic chiasm in a patient with bitemporal visual field loss. To our knowledge, these neuroimaging findings have not been previously described in association with ethambutol therapy.

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 score0.008
Threshold uncertainty score0.016

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 integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.294
Teacher spread0.261 · 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

Citations34
Published2014
Admission routes1
Has abstractyes

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