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Record W2028442901 · doi:10.1002/mds.20515

Absence of previously reported variants in the <i>SCNA</i> (G88C and G209A), <i>NR4A2</i> (T291D and T245G) and the <i>DJ</i>‐<i>1</i> (T497C) genes in familial Parkinson's disease from the <i>Gene</i>PD study

2005· article· en· W2028442901 on OpenAlexaff
Samer Karamohamed, Lawrence I. Golbe, M. H. Mark, Alice Lazzarini, Oksana Suchowersky, N. Labelle, Mark Guttman, L. J. Currie, G. Frederick Wooten, Mark Stacy, Marie Saint‐Hilaire, Robert G. Feldman, J. Liu, Christina M. Shoemaker, Jemma B. Wilk, Anita L. DeStefano, Jeanne C. Latourelle, Gang Xu, Ray L. Watts, John H. Growdon, Michael S. Lew, Cheryl Waters, P. Vieregge, Peter P. Pramstaller, Christine Klein, Brad A. Racette, Joel S. Perlmutter, A. Parsian, Carlos Singer, Erwin B. Montgomery, Kenneth B. Baker, James F. Gusella, Alan Herbert, Richard H. Myers

Bibliographic record

VenueMovement Disorders · 2005
Typearticle
Languageen
FieldNeuroscience
TopicNuclear Receptors and Signaling
Canadian institutionsUniversity of TorontoUniversity of Calgary
FundersNational Institute of Neurological Disorders and Stroke
KeywordsParkinson's diseaseProbandGeneticsGeneDiseaseBiologyMedicineMutationInternal medicine

Abstract

fetched live from OpenAlex

Parkinson's disease (PD) is a neurodegenerative disorder in which relatives of the probands are affected approximately 4 times as frequently as relatives of control subjects. Several genes have been implicated as genetic risk factors for PD. We investigated the presence of six reported genetic variations in the SCNA, NR4A2, and DJ-1 genes in 292 cases of familial Parkinson's disease from the GenePD study. None of the variants were found in the GenePD families. Our results suggest that other variants or genes account for the familial risk of PD within the GenePD study.

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)0.002
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.231
Teacher spread0.216 · 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

Citations15
Published2005
Admission routes1
Has abstractyes

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