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Record W1893021881 · doi:10.1684/epd.2015.0759

Insight into the precuneus: a novel seizure semiology in a child with epilepsy arising from the right posterior precuneus

2015· article· en· W1893021881 on OpenAlexaff
Janette Mailo, Richard Tang‐Wai

Bibliographic record

VenueEpileptic Disorders · 2015
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPrecuneusPsychologyEpilepsyNeuroscienceIctalCognitive psychologyAudiologyMedicineFunctional magnetic resonance imaging

Abstract

fetched live from OpenAlex

To date, there is limited understanding of the role of the precuneus. fMRI studies have suggested its involvement in a wide spectrum of highly integrated tasks, including spatially-guided behaviour, visuo-spatial imagery, and consciousness. We present a patient with intractable parietal lobe epilepsy arising from a lesion localized to the right precuneus. Two seizure types with distinct semiologies were captured on video-EEG monitoring. The first type consisted of an urge described as a "feeling of wanting to move". On video analysis, the patient is seen to turn his head and body to his left. He remains conscious, he is able to answer questions and when asked, he can look to his right. This seizure was associated with an ictal pattern localized to the right parieto-occipital region. The second seizure type consisted of reading-induced visual distortion with macropsia and micropsia. Interictally, intermittent rhythmic slowing and spikes were seen and localized to the parietal midline and the right parieto-occipital regions. Our patient's seizures are positive phenomena of the right precuneus and its related processing network. They represent unique seizure semiologies that offer further insight into the role of the precuneus in spatial awareness, visuo-spatial processing and consciousness.

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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.279
Teacher spread0.250 · 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

Citations17
Published2015
Admission routes1
Has abstractyes

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