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Evidence Favoring Genetic Heterogeneity for Febrile Convulsions

2000· article· en· W2055781127 on OpenAlexaffabout
Lemuel Racacho, Richard S. McLachlan, George C. Ebers, John Maher, Dennis E. Bulman

Bibliographic record

VenueEpilepsia · 2000
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of ManitobaLondon Health Sciences CentreHealth Sciences CentreOttawa Hospital
Fundersnot available
KeywordsJuvenile myoclonic epilepsyEpilepsyConvulsionMyoclonic JerkLocus (genetics)Febrile convulsionsGenetic linkageMyoclonusGenetic heterogeneityNeurological disorderGeneticsIdiopathic generalized epilepsyBiologyCentral nervous system diseaseNeurosciencePhenotypeGene

Abstract

fetched live from OpenAlex

PURPOSE: Two large Canadian kindreds appearing to segregate febrile convulsions as an autosomal dominant trait were evaluated for linkage to three known FC loci, as well as other epilepsy loci. METHODS: Members of the two families were genotyped with microsatellite markers linked to the previously identified febrile convulsion loci, FEB1, FEB2, and GEFS+, and we performed two-point linkage analyses by assuming an autosomal dominant mode of inheritance. RESULTS: We report the exclusion of the FC trait in our families to FEB1 on 8q13-21 and to a second febrile convulsion locus on 19p13. Furthermore, we also excluded the GEFS+ locus on 19q13.1 as the cause of febrile convulsions in both kindreds. Microsatellite markers linked to juvenile myoclonic epilepsy (EJM1), benign neonatal familial convulsions EBN1 and EBN2, autosomal dominant nocturnal frontal lobe epilepsy (ADNFLE), idiopathic generalized epilepsy (EGI), progressive myoclonic epilepsy of Unverricht-Lundborg (EPM1), and partial epilepsy with auditory features (EPT), were also excluded as potential loci linked to the FC trait in our families. CONCLUSIONS: These findings favor considerable genetic heterogeneity for febrile convulsions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.999

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)0.0020.001

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 head0.081
GPT teacher head0.360
Teacher spread0.279 · 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.

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

Citations24
Published2000
Admission routes2
Has abstractyes

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