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Record W2098479956 · doi:10.1002/mds.10126

Genetic and clinical heterogeneity in paroxysmal kinesigenic dyskinesia: Evidence for a third EKD gene

2002· article· en· W2098479956 on OpenAlexaff
Sian Spacey, Enza Maria Valente, Gurusidheshwar M. Wali, Thomas T. Warner, Paul Jarman, Anthony H.V. Schapira, Peter Dixon, Mary B. Davis, Kailash P. Bhatia, Nicholas Wood

Bibliographic record

VenueMovement Disorders · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsParoxysmal dyskinesiaDyskinesiaMedicineGeneticsNeurosciencePsychologyInternal medicineBiologyParkinson's diseaseDisease

Abstract

fetched live from OpenAlex

Paroxysmal kinesigenic dyskinesia (PKD) is characterised by paroxysms of choreic, dystonic, ballistic, or athetoid movements. The attacks typically last seconds to minutes in duration and are induced by sudden voluntary movement. PKD loci have been identified on chromosome 16. We present the clinical and genetic details of two British and an Indian family with PKD. Linkage to the PKD loci on chromosome 16 has been excluded in one of these families, providing evidence for a third loci for PKD. Detailed clinical descriptions highlight the presence of both adolescent and infantile seizures in some of the PKD families. This study attempts to clarify the relationship of adolescent and infantile seizures to PKD and provides evidence that PKD is both genetically and clinically heterogeneous.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score1.000

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 head0.042
GPT teacher head0.302
Teacher spread0.260 · 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

Citations79
Published2002
Admission routes1
Has abstractyes

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