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Record W2156235611 · doi:10.1109/iembs.2002.1053206

Transient analysis of non-linear VOR nystagmus - clinical implications

2002· article· en· W2156235611 on OpenAlexaff
Heather Smith, W.W.P. Chan, Henrietta L. Galiana

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsVestibular systemNystagmusVestibulo–ocular reflexReflexEye movementTransient (computer programming)AudiologyElectrooculographyTime constantIntegratorComputer scienceControl theory (sociology)MedicinePsychologyArtificial intelligenceNeuroscienceEngineering

Abstract

fetched live from OpenAlex

We present an alternate method for the analysis of eye movements in the vestibular ocular reflex (VOR), called vestibular nystagmus. Classically, a central 'integrator' (gaze holding) is assumed to have a large time constant, so that VOR dynamics are presumed to be seen in the behaviour of 'envelopes' of slow-phase eye velocity. This method often cannot distinguish between healthy normals and compensated patients, and theoretically it is inappropriate in a switched system like the VOR. Our transient analysis method instead allows for simultaneous estimation of central and vestibular time constants, by incorporating the effects of transients in each slow-phase segment. We analyzed data from both unilateral vestibular patients and normal subjects to illustrate the effects of various analysis methods on estimated VOR parameters. The new method allows for robust detection of vestibular abnormalities even after compensation, and can be used for the analysis of any eye reflexes.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.092
GPT teacher head0.360
Teacher spread0.268 · 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 designObservational
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

Citations2
Published2002
Admission routes1
Has abstractyes

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