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Paroxysmal eyelid movements

2004· article· en· W2138178342 on OpenAlexaff
C. Camfield, P. R. Camfield, Martin Sadler, Susan R. Rahey, K Farrell, S. Chayasirisobbon, Ingrid E. Scheffer

Bibliographic record

VenueNeurology · 2004
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsVictoria General Hospital
Fundersnot available
KeywordsEyelidEpilepsyGeneralized epilepsyConfusionMedicineNeurologyPediatricsElectroencephalographyPsychologySurgeryPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Persistent, frequent, nonepileptic paroxysmal eyelid movements were observed in 19 children and adults with well-controlled generalized epilepsy. METHODS: Patients were identified from five epilepsy centers. RESULTS: Seventeen patients were female and two male. All had generalized photosensitive epilepsy requiring antiepileptic drugs (AEDs). In two children, paroxysmal eyelid movements began 2 to 4 years before their epilepsy was noted; in the remainder, it was noted when epilepsy was first diagnosed. Age at last follow-up was 8 to 38 years (average 21 years) with average follow-up of 9 years. All patients showed photosensitive generalized spike-wave discharges on EEG. Paroxysmal eyelid movements were a source of diagnostic confusion, but direct examination and video during EEG recording distinguished the attacks from absence seizures. In all cases, the epilepsy is completely or nearly completely controlled with AEDs, but the paroxysmal eyelid movements have not resolved with age. In 12 cases, there was a family history of the eyelid disorder without epilepsy. Videos of patients and an affected parent are available on the Neurology Web site. CONCLUSION: There is an association between paroxysmal eyelid movements and photosensitive generalized epilepsy, creating diagnostic confusion.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
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)0.0020.000

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 head0.022
GPT teacher head0.308
Teacher spread0.287 · 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

Citations26
Published2004
Admission routes1
Has abstractyes

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