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Encephalopathy and<i>SCN1A</i>mutations

2011· article· en· W1567812138 on OpenAlexfundno aff
Shan Tang, Jean‐Pierre Lin, Elaine Hughes, Ata Siddiqui, Ming Lim, Karine Lascelles

Bibliographic record

VenueEpilepsia · 2011
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
FundersHospital for Sick Children
KeywordsStatus epilepticusEpilepsyMedicineEncephalopathyWhite matterNeuroscienceEpileptogenesisMutationAnesthesiaInternal medicinePsychologyMagnetic resonance imagingBiologyGenetics

Abstract

fetched live from OpenAlex

We describe three children with genetically different sodium channel alpha 1 subunit (SCN1A) mutation associated epilepsy who experienced a sudden and sustained neurologic regression following status epilepticus in two and acute sepsis in one. Neuroimaging showed evidence of cerebral ischemia in one, but the other two cases showed cerebellar signal abnormalities. The selectivity of cerebellar white matter change suggests a different mechanism of injury or increased susceptibility of this brain region to injury in at least some patients with SCN1A mutations. This report adds to the spectrum and mechanism of acute neurologic deterioration and functional deficit associated with SCN1A mutations, which remains to be fully understood.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.044
GPT teacher head0.289
Teacher spread0.244 · 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

Citations18
Published2011
Admission routes1
Has abstractyes

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