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Record W2055271234 · doi:10.1177/088307380101600401

Topical Review: Magnetoencephalography and Magnetic Source Imaging in Children

2001· review· en· W2055271234 on OpenAlexaff
Hiroshi Otsubo, O. Carter Snead

Bibliographic record

VenueJournal of Child Neurology · 2001
Typereview
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMagnetoencephalographyMagnetic resonance imagingNeuroscienceFunctional magnetic resonance imagingNeuroimagingEpilepsyElectroencephalographyPsychologyMedicineRadiology

Abstract

fetched live from OpenAlex

Magnetoencephalography is a technique that detects the magnetic fields associated with the intracellular current flow within neurons, unlike electroencephalography, which measures extracellular volume currents. Superconducting quantum interference devices are used to amplify these very small magnetic field signals. Magnetic source imaging is the combination of functional data derived from magnetoencephalographic recordings coregistered with structural magnetic resonance imaging (MRI). The utility of magnetic source imaging lies in the combination of the submillisecond temporal resolution of magnetoencephalography with the precise anatomic images provided by magnetic resonance imaging. As such, magnetic source imaging is a useful tool for noninvasive localization of the epileptogenic zone in children who are candidates for epilepsy surgery. Similarly, using magnetoencephalographic recordings with evoked and event-related potentials, magnetic source imaging holds great promise as a noninvasive method for precise localization of somatosensory, motor, language, visual, and auditory cortex. Finally, magnetic source imaging is proving a valuable research tool in the investigation of epilepsy, head trauma, brain plasticity, and disorders of language, memory, cognition, and executive function in children.

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)0.000
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 score0.926
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.013
GPT teacher head0.313
Teacher spread0.299 · 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

Citations44
Published2001
Admission routes1
Has abstractyes

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