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Record W4403244177 · doi:10.1152/jn.00217.2024

Ictal and interictal epileptic networks of 34 patients with hypothalamic hamartoma on scalp electroencephalography

2024· article· en· W4403244177 on OpenAlexaff
Sarah Metzger, Julia Jacobs, Friederike Niedermoser, Peter C. Reinacher, Kathrin Wagner, Jan Schönberger, Lisa Rieder, Andreas Schulze‐Bonhage, Kerstin Alexandra Klotz

Bibliographic record

VenueJournal of Neurophysiology · 2024
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersUniversité de Fribourg
KeywordsIctalElectroencephalographyHypothalamic hamartomaNeuroscienceScalpEpilepsyPsychologyGelastic seizureMedicineAudiologyInternal medicineAnatomy

Abstract

fetched live from OpenAlex

Data from routine long-term video-EEG (VEEG) monitoring can be used to visualize and analyze networks of cortical involvement in patients with hypothalamic hamartoma. Involvement of temporal cortex areas is frequent even in patients with relatively mild disease and might be an early sign of dissemination. Repeated VEEGs in eight patients show an overall increase in seizure activity and interictal epileptiform discharges (IEDs) and changes in the networks of cortical involvement over time.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
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)0.0010.000

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 head0.007
GPT teacher head0.242
Teacher spread0.235 · 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 designObservational
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

Citations2
Published2024
Admission routes1
Has abstractyes

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