MétaCan
Menu
Back to cohort
Record W2100251996 · doi:10.1212/cpj.0b013e3182a1ba12

Emerging devices for epilepsy

2013· article· en· W2100251996 on OpenAlexaboutno aff
Chrystal M. Reed, Michael Gruenthal

Bibliographic record

VenueNeurology Clinical Practice · 2013
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsVagus nerve stimulationFood and drug administrationEpilepsyContext (archaeology)MedicineDrug Resistant EpilepsyIntensive care medicineEpilepsy surgeryPharmacologyVagus nervePsychiatryStimulationInternal medicine

Abstract

fetched live from OpenAlex

About 30% of people with epilepsy continue to have seizures despite a growing array of antiseizure drugs. For some of these people, surgical resection of brain tissue is an effective therapeutic option. For others, the likelihood of seizure freedom is low, and has not improved much despite the introduction of several new antiseizure drugs. The vagus nerve stimulator is the only device approved by the Food and Drug Administration (FDA), but it rarely results in freedom from seizures. Recently, 2 approaches to electrical stimulation of the brain have been reported. One device has been approved for use in Canada and in Europe, and it seems likely that one or more such devices will be approved for use in the United States. We examine some of the data from these studies in the context of the current FDA-approved drugs and devices.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.040
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0400.013

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 head0.074
GPT teacher head0.434
Teacher spread0.361 · 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
GenreReview

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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueNeurology Clinical PracticeSame topicNeurological disorders and treatmentsFrench-language works237,207