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Record W2340115544 · doi:10.1080/14737175.2016.1181544

The role of MEG in pre-surgical evaluation of epilepsy: current use and future directions

2016· review· en· W2340115544 on OpenAlexaff
Raheel Ahmed, James T. Rutka

Bibliographic record

VenueExpert Review of Neurotherapeutics · 2016
Typereview
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMagnetoencephalographyEpilepsyEpilepsy surgeryMedicinePerioperativeSurgical resectionNeuroscienceElectroencephalographyPsychologyRadiology

Abstract

fetched live from OpenAlex

Identification of the epileptogenic zone is a critical determinant of seizure control outcomes following surgical resection in medically refractory seizures. There has been increasing recognition of the contributive value of Magnetoencephalography (MEG) studies in the diagnostic evaluation of epilepsy. Biomagnetic signals recorded by MEG studies in combination with source modeling techniques can yield diagnostic information regarding the underlying epileptogenic zone. MEG evaluation is particularly useful in evaluation of non lesional neocortical epilepsy. In these cases, MEG spike sources can guide presurgical and perioperative invasive monitoring. The incorporation of MEG-based diagnostic information into the surgical evaluation and management plan has consistently been shown to be associated with improved seizure control outcomes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.099
GPT teacher head0.454
Teacher spread0.356 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations6
Published2016
Admission routes1
Has abstractyes

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