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Record W3006743642 · doi:10.1177/0883073819901228

Misleading Focal Clinical, Neurophysiologic, and Imaging Features in 2 Children With Generalized Epilepsy Who Underwent Invasive Electroencephalographic (EEG) Monitoring

2020· article· en· W3006743642 on OpenAlexaff
Duaa Baarmah, Puneet Jain, Robyn Whitney, Elizabeth Donner, James M. Drake, Cristina Go, O. Carter Snead, Shelly K. Weiss, Elysa Widjaja, Eriko Yamamoto, Annette Ye, Haruka Yamasaki, Ayako Ochi

Bibliographic record

VenueJournal of Child Neurology · 2020
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsSickKids FoundationUniversity of TorontoMcMaster UniversityHospital for Sick Children
Fundersnot available
KeywordsElectroencephalographyEpilepsyNeuroimagingGeneralized epilepsyHyperventilationMedicinePsychologyNeuroscienceAnesthesia

Abstract

fetched live from OpenAlex

Children and adults with genetic generalized epilepsy may have focal clinical seizure symptoms as well as electroencephalographic (EEG) findings. This may pose a diagnostic challenge to clinicians, especially when concomitant focal neuroimaging findings exist and the epilepsy is medically refractory. We sought to highlight the challenges that clinicians may face through the description of 2 children with suspected genetic generalized epilepsy who had both focal seizure symptoms and EEG/neuroimaging findings and underwent invasive EEG monitoring. Ultimately, invasive monitoring failed to demonstrate a focal origin for the seizures in both cases, and instead confirmed the presence of genetic generalized epilepsy. We demonstrate that ≥3-Hz generalized monomorphic spike and waves are less likely to represent secondary bilateral synchrony, that focal neuroimaging findings may not always be causal and that repeated hyperventilation is an essential activation procedure for genetic generalized epilepsy.

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)0.003
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
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 head0.019
GPT teacher head0.297
Teacher spread0.278 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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