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Record W1519491988 · doi:10.1684/epd.2008.0184

Ictal fear depends on the cerebral laterality of the epileptic activity

2008· article· en· W1519491988 on OpenAlexaff
Anik Guimond, Claude M. J. Braun, Émilie Bélanger, Isabelle Rouleau

Bibliographic record

VenueEpileptic Disorders · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsIctalLateralityPsychologyFocus (optics)Lateralization of brain functionEpilepsyTemporal lobeAudiologyElectroencephalographyPerceptionNeuroscienceMedicinePhysics

Abstract

fetched live from OpenAlex

Glascher and Adolph (2003) proposed that both amydalae are specialized for fear, but that the right one is a fast, short, and relatively automatic fear processor, whereas the left one is more detail-oriented and perceptual-cognitive. According to this model, early ictal fear should occur more often in cases with a right temporal lobe epileptic focus. Several authors have tried to find a hemispheric specialization for ictal fear, but have not reached the power to attain a statistically significant effect of focus side. In this study, using previously published cases of unilateral epileptic focus causing early ictal symptoms of fear, we found 144 cases, of which 98 had a right hemisphere focus (68%) and 46 having left hemisphere focus (32%, p < 0.0005). Several control variables were assembled to verify possible alternative explanations of the main effect.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.108
GPT teacher head0.316
Teacher spread0.208 · 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 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

Citations26
Published2008
Admission routes1
Has abstractyes

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