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Diffusion tensor imaging in temporal lobe epilepsy

2011· review· en· W1545733638 on OpenAlexafffund
Donald Gross

Bibliographic record

VenueEpilepsia · 2011
Typereview
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsHealth Sciences CentreUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsTemporal lobeDiffusion MRIWhite matterEpilepsyNeurosciencePsychologyNeuroimagingMedicineMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

Although mesial temporal sclerosis (MTS) has long been recognized in association with temporal lobe epilepsy (TLE), there is a growing body of literature suggesting structural abnormalities extending beyond the temporal lobe in patients with TLE. Diffusion tensor imaging (DTI) is a novel imaging technique that provides insight into the structural integrity of cerebral white matter. DTI studies have demonstrated extensive bilateral white matter abnormalities in TLE that extend far beyond the temporal lobe, even in patients with unilateral MTS. The relationship between white matter abnormalities, seizures, and comorbidity in TLE remains unclear.

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)0.001
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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0050.005
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.137
GPT teacher head0.403
Teacher spread0.267 · 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

Citations139
Published2011
Admission routes2
Has abstractyes

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