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Record W2315424398 · doi:10.1017/s0317167100016905

Neurofilament M gene in a French-Canadian Population with Parkinson’s Disease

2005· article· en· W2315424398 on OpenAlexafffundvenueabout
Fabin Han, Dennis E. Bulman, Michel Panisset, David A. Grimes

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsMcGill UniversityOttawa HospitalUniversity of Ottawa
FundersParkinson Society Canada
KeywordsMutationGeneticsParkinson's diseaseGene mutationHeterozygote advantageCompound heterozygosityDiseasePopulationDegenerative diseaseGeneBiologyMedicineAlleleInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Recently, a single base pair substitution (G1747A) mutation of the neurofilament M (NF-M) gene was reported in a French-Canadian patient with early onset Parkinson's disease (PD). Three unaffected siblings were found to be heterozygotes for the NF-M Gly336Ser mutation but, to date, no other affected PD individuals have been found with a similar mutation. No other individuals with Parkinson's disease and of similar ethnic background have been screened for this mutation. METHODS: We screened 102 French-Canadian patients with definite PD and 45 French-Canadian controls for this substitution in the NF-M gene using a PCR-restriction enzyme digestion method. RESULTS: None of the patients or controls carried this mutation. CONCLUSION: Our results would indicate that this mutation is not common even in a PD population of similar ethnic background and suggest this change represents a rare variant. However, these results do not exclude the possibility that other mutations in this gene could be present.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0060.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.259
Teacher spread0.239 · 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

Citations13
Published2005
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicSkin and Cellular Biology ResearchFrench-language works237,207