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Record W2022844317 · doi:10.1017/s0317167100014232

The Role of the Cerebellum in the Pathophysiology of Parkinson's Disease

2013· review· en· W2022844317 on OpenAlexafffundvenue
Mechelle M. Lewis, Shawna Galley, Samantha Johnson, James K. R. Stevenson, Xuemei Huang, Martin J. McKeown

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2013
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of British Columbia
FundersNational Center for Research ResourcesCalifornia HIV/AIDS Research ProgramNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchDeutsches KrebsforschungszentrumNational Institute on Aging
KeywordsPars compactaSubstantia nigraBasal gangliaCerebellumParkinson's diseaseNeurosciencePathophysiologyDopaminergicDegenerative diseasePsychologyDiseaseMedicinePathologyCentral nervous system diseaseDopamineCentral nervous system

Abstract

fetched live from OpenAlex

Parkinson's disease (PD), the most common neurodegenerative movement disorder, has traditionally been considered a "classic" basal ganglia disease, as the most obvious pathology is seen in the dopaminergic cells in the substantia nigra pars compacta. Nevertheless recent discoveries in anatomical connections linking the basal ganglia and the cerebellum have led to a re-examination of the role of the cerebellum in the pathophysiology of PD. This review summarizes the role of the cerebellum in explaining many curious features of PD: the significant variation in disease progression between individuals; why severity of dopaminergic deficit correlates with many features of PD such as bradykinesia, but not tremor; and why PD subjects with a tremor-predominant presentation tend to have a more benign prognosis. It is clear that the cerebellum participates in compensatory mechanisms associated with the disease and must be considered an essential contributor to the overall pathophysiology of 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 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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.809
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.008
Scholarly communication0.0000.000
Open science0.0040.000
Research integrity0.0000.002
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 head0.037
GPT teacher head0.288
Teacher spread0.251 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations81
Published2013
Admission routes3
Has abstractyes

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