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Record W4281935740 · doi:10.1017/9781108772396.009

Clinical Presentation of Insulo-Opercular Epilepsy in Children

2022· book-chapter· en· W4281935740 on OpenAlexaff
Michael Duchowny, Delphine Taussig, Petia Dimova

Bibliographic record

VenueCambridge University Press eBooks · 2022
Typebook-chapter
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsIctalSemiologyEpilepsy surgeryPsychologyPathologicalEpilepsyMedicineTemporal lobeNeurosciencePathology

Abstract

fetched live from OpenAlex

Surgery for medically intractable childhood seizures originating in the opercular-insular cortex has only been undertaken in the last decade. While the need for SEEG interrogation and rates of post-operative seizure-freedom in children are comparable to adults, several important differences distinguish the pediatric experience. Most pediatric surgical candidates are pre-verbal or non-verbal and cannot describe subjective sensory or affective seizure manifestations. There is a higher representation of frontal lobe seizure semiology compared to adults, whereas ictal and inter-ictal electrographic discharges are typically more widespread throughout the cerebral hemisphere. Cortical malformations constitute the primary underlying pathological finding in the majority of pediatric cases. The recent surgical success in medically refractory children provides a compelling rationale to pursue further clinical studies and offer surgical candidacy in selected 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)0.000
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.035
GPT teacher head0.285
Teacher spread0.250 · 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
GenreOther

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
Published2022
Admission routes1
Has abstractyes

Explore more

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