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Use and Abuse of EEG in the Diagnosis of Idiopathic Generalized Epilepsies

2005· review· en· W1967824965 on OpenAlexaff
Michael Koutroumanidis, Shelagh Smith

Bibliographic record

VenueEpilepsia · 2005
Typereview
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsIctalElectroencephalographyIdiopathic generalized epilepsyMedicineEpilepsyPsychologyNeuroscience

Abstract

fetched live from OpenAlex

This article concentrates on the role of electroencephalograms (EEGs) in the diagnosis and management of patients with idiopathic generalized epilepsies (IGEs). We review the morphologic and behavioral characteristics of the interictal and ictal EEG markers of IGE that should guide recording strategies to augment its diagnostic yield, and we attempt to delineate those particular features that may be relevant to different IGE syndromes. We also explore the electrographic boundaries between IGEs and cryptogenic/symptomatic generalized and focal epilepsies, and focal/secondary generalized epilepsies, with particular relevance to the phenomena of focal abnormalities and secondary bilateral synchrony, commenting on possible diagnostic pitfalls and areas of uncertainty.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.002

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 head0.113
GPT teacher head0.380
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations52
Published2005
Admission routes1
Has abstractyes

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