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Record W4225415811 · doi:10.1111/epi.17240

International League Against Epilepsy classification and definition of epilepsy syndromes with onset at a variable age: position statement by the ILAE Task Force on Nosology and Definitions

2022· article· en· W4225415811 on OpenAlexafffund
Kate Riney, Alicia Bogacz, Ernest Somerville, Édouard Hirsch, Rima Nabbout, Ingrid E. Scheffer, Sameer M. Zuberi, Taoufik Alsaadi, Jacqueline A. French, Nicola Specchio, Eugen Trinka, Samuel Wiebe, Stéphane Auvin, Leonor Cabral‐Lim, Ansuya Naidoo, Emilio Perucca, Solomon L. Moshé, Elaine Wirrell, Paolo Tinuper

Bibliographic record

VenueEpilepsia · 2022
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchCumming School of Medicine, University of CalgaryAllerganNational Institutes of HealthArvelle TherapeuticsNeuraxpharmEpilepsiatutkimussäätiöSunovionH. Lundbeck A/SUCB PharmaG.L. PharmaEVER Neuro PharmaOtsuka PharmaceuticalMarinus PharmaceuticalsAlberta InnovatesEisaiAustrian Science FundGreenwich BiosciencesBundesministerium für Wissenschaft und ForschungZynerba PharmaceuticalsSanofiGW PharmaceuticalsBiogenPfizerLivaNovaGlaxoSmithKlineZogenixEuropean CommissionU.S. Department of DefenseEli Lilly and CompanySK Life ScienceNational Institute of Neurological Disorders and StrokeUniversity of Calgary
KeywordsNosologyEpilepsyEpilepsy syndromesEtiologyPsychologyPsychiatryElectroencephalographyPediatricsMedicine

Abstract

fetched live from OpenAlex

The goal of this paper is to provide updated diagnostic criteria for the epilepsy syndromes that have a variable age of onset, based on expert consensus of the International League Against Epilepsy Nosology and Definitions Taskforce (2017-2021). We use language consistent with current accepted epilepsy and seizure classifications and incorporate knowledge from advances in genetics, electroencephalography, and imaging. Our aim in delineating the epilepsy syndromes that present at a variable age is to aid diagnosis and to guide investigations for etiology and treatments for these patients.

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)0.008
metaresearch head score (Gemma)0.016
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.039
GPT teacher head0.283
Teacher spread0.243 · 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
GenreMethods

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

Citations260
Published2022
Admission routes2
Has abstractyes

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