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Record W4390717649 · doi:10.1212/cpj.0000000000200267

It Is Time to Talk About Mortality in People With Functional Seizures

2024· editorial· en· W4390717649 on OpenAlexaff
Mark R. Keezer, Adriana Bermeo‐Ovalle

Bibliographic record

VenueNeurology Clinical Practice · 2024
Typeeditorial
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsEpilepsyStatus epilepticusMedicineDiseasePopulationAffect (linguistics)PsychiatryPediatricsPsychologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Epilepsy is associated with an increased risk of death, as compared with otherwise similar individuals from the general population.This is true for people with active and drug-resistant epilepsy, but also true for individuals with idiopathic and drug-responsive epilepsy.1 Seizurerelated causes of death such as sudden unexpected death in epilepsy (SUDEP), status epilepticus, and drowning are devastating.They generally affect younger individuals and result in many years of life lost.However, most premature deaths among people with epilepsy are related to comorbid conditions. 2 People with epilepsy are at a greater risk of developing cancer and cardiovascular disease.

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)0.030
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.017
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.030
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0030.001
Science and technology studies0.0030.003
Scholarly communication0.0070.007
Open science0.0040.002
Research integrity0.0170.029
Insufficient payload (model declined to judge)0.0140.012

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 head0.045
GPT teacher head0.438
Teacher spread0.393 · 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
GenreEditorial

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
Published2024
Admission routes1
Has abstractyes

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