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Record W2184472594 · doi:10.1159/000442021

Familial Aggregation and Co-Aggregation of Essential Tremor and Parkinson's Disease

2015· article· en· W2184472594 on OpenAlexaff
Elan D. Louis, Lorraine N. Clark, Ruth Ottman

Bibliographic record

VenueNeuroepidemiology · 2015
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsColumbia College
FundersNational Institute of Neurological Disorders and StrokeNational Human Genome Research InstituteNational Institute on Aging
KeywordsProbandMedicineFamily aggregationParkinson's diseaseInternal medicineDiseaseEssential tremorGastroenterologyGeneticsPsychiatryMutationBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Current data suggest that the 2 common tremor disorders, essential tremor (ET) and Parkinson's disease (PD), may be associated with one another. Familial aggregation studies allow one to further explore their relatedness. METHODS: Probands with ET (n = 110), PD (n = 130) or both ET and PD (n = 27) and control probands (n = 177) reported whether they had relatives with these diseases or with non-specific tremor. RESULTS: A greater proportion of ET probands than control probands reported relatives with ET (30.0 vs. 2.8%, p < 0.001), non-specific tremor (38.2 vs. 13.6%, p < 0.001) and both ET and PD in different relatives (6.4 vs. 0.6%, p = 0.004). A greater proportion of PD probands than control probands reported relatives with PD (20.0 vs. 8.5%, p = 0.003), ET (11.5 vs. 2.8%, p = 0.002) and both ET and PD in different relatives (6.9 vs. 0.6%, p = 0.002). CONCLUSIONS: This study provides evidence for the aggregation of ET in ET families and PD in PD families, and the familial co-aggregation of ET and PD.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.318
Teacher spread0.274 · 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

Citations19
Published2015
Admission routes1
Has abstractyes

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