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Record W2063452696 · doi:10.1097/rlu.0b013e3181c7c17c

F-18 FDG Brain PET and Tc-99m ECD Brain SPECT in a Patient With Multiple Recurrent Epileptic Seizures

2010· article· en· W2063452696 on OpenAlexaff
Sophie Turpin, Raymond Lambert, Josée Dubois, Paola Diadori

Bibliographic record

VenueClinical Nuclear Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsIctalMedicinePositron emission tomographyHypermetabolismNuclear medicineIctal-Interictal SPECT Analysis by SPMMagnetic resonance imagingFluorodeoxyglucoseEpilepsyRadiologyInternal medicine

Abstract

fetched live from OpenAlex

The combination of interictal brain fluorine-18 fluorodeoxyglucose positron emission tomography (F18-FDG PET) and ictal brain Tc-99m ethylcysteinate dimer (ECD) SPECT is currently used for identification of epileptic foci. Usually, hypometabolism is demonstrated on the F-18 FDG PET and hyperperfusion in the same region on the Tc-99m ECD ictal SPECT. The authors report a rare occurrence of left frontal hypermetabolism in a young girl with multiple recurring epileptic seizures, on F18-FDG PET, which was confirmed on ictal Tc-99m ECD SPECT. The patient's seizures were characterized by head deviation and movements of the upper extremities. The seizures were occurring non stop every 3 to 5 minutes, even during imaging, lasting about 15 seconds. Magnetic resonance imaging (MRI) showed evidence of dysplastic cortex which was consistent with the focal abnormalities on PET and SPECT.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.038
GPT teacher head0.381
Teacher spread0.343 · 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 designCase report
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

Citations3
Published2010
Admission routes1
Has abstractyes

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