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Record W2758582532 · doi:10.7759/cureus.1735

White Matter Tracts in Patients with Temporal Lobe Epilepsy: Pre- and Postoperative Assessment

2017· article· en· W2758582532 on OpenAlexaff
Fateme Salehi, Manas Sharma, Terry M. Peters, Ali R. Khan

Bibliographic record

VenueCureus · 2017
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsCorpus callosumMedicineWhite matterTemporal lobeLateralization of brain functionEpilepsyMagnetic resonance imagingRadiologySurgeryAnatomyAudiologyPsychiatry

Abstract

fetched live from OpenAlex

Patients with intractable temporal lobe epilepsy (TLE) undergo surgical resection of the anterior temporal lobe. Preoperative assessment of TLE patients involves a multidisciplinary assessment and may involve the use of invasive electroencephalogram (EEG) recording for lateralization of seizure focus in ambiguous cases. Understanding the white matter fibre tracts affected in TLE may assist in preoperative lateralization and planning. We studied pre- and postoperative white matter fibre tract changes in six patients with TLE who underwent surgical resection. Our results indicate that changes in the corpus callosum are highly specific, with the ability to lateralize the epileptogenic side in 100% of our patients (six of six). Contralateral changes were found in all patients with variable involvement of white matter tracts. Postoperatively, most patients (five of six) exhibited further changes to the tracts on the ipsilateral side, with three patients showing contralateral abnormalities. We provide a detailed assessment of pre- and postoperative white matter fibre tracts in patients with TLE and confirm that abnormalities in the ipsilateral corpus callosum may aid in preoperative lateralization and obviate the need for invasive EEG monitoring.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.015
GPT teacher head0.318
Teacher spread0.304 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2017
Admission routes1
Has abstractyes

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