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Record W1978131871 · doi:10.1155/2011/148394

Evaluating the Use of Optical Coherence Tomography in Optic Neuritis

2011· article· en· W1978131871 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMultiple Sclerosis International · 2011
Typearticle
Languageen
FieldMedicine
TopicRetinal and Optic Conditions
Canadian institutionsUniversity of Calgary
FundersMultiple Sclerosis SocietyMultiple Sclerosis Society of CanadaStem Cell Network
KeywordsOptic neuritisMultiple sclerosisNerve fiber layerOptical coherence tomographyMedicineOptic nerveNeuroscienceRetinalMyelinAfferentGlaucomaCentral nervous systemOphthalmologyAnatomyBiologyImmunology

Abstract

fetched live from OpenAlex

Optic neuritis (ON) is an inflammatory optic nerve injury, which is strongly associated with multiple sclerosis (MS). Axonal damage in the optic nerve manifests as retinal nerve fiber layer (RNFL) deficits, which can be readily quantified with optical coherence tomography (OCT). The RNFL represents the most proximal region of the afferent visual pathway; and, as such, is a unique region of the central nervous system (CNS) because it lacks myelin. Changes in retinal integrity can be correlated with reliable and quantifiable visual outcomes to provide a structural-functional paradigm of CNS injury. Because the eye provides a unique "view" into the effects of CNS inflammation, the ON "system model" may provide greater understanding about disease mechanisms, which underpin disability in MS. This review addresses the applications of OCT in study of ON patients, with specific reference to the published reports to date. The future role of OCT is discussed, both in terms of the potential gains and certain challenges associated with this evolving technology.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.754

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.322
GPT teacher head0.343
Teacher spread0.021 · 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