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Record W2051715381 · doi:10.1055/s-2001-13116

Functional Imaging in Parkinson's Disease

2001· review· en· W2051715381 on OpenAlexaff
Alain Dagher

Bibliographic record

VenueSeminars in Neurology · 2001
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsPositron emission tomographyMedicineNeuroimagingParkinson's diseaseFunctional imagingNeuroscienceFunctional neuroimagingBasal gangliaSingle-photon emission computed tomographyDiseaseEmission computed tomographyDopamineDeoxyglucoseNuclear medicineRadiologyPathologyInternal medicineCentral nervous systemPsychologyPsychiatry

Abstract

fetched live from OpenAlex

This article reviews the applications of functional neuroimaging with positron emission tomography (PET) and single photon emission computed tomography (SPECT) to the diagnosis and treatment of Parkinson's disease (PD). PET measurements with [18F]deoxyglucose to measure glucose metabolism or with various markers of the pre- and postsynaptic dopamine systems may distinguish idiopathic PD from other conditions presenting with an akinetic-rigid state. Moreover, PET has been used to gain new insights into mechanisms of cell death and the role of heredity in Parkinson's disease. Finally, we discuss the use of functional neuroimaging to study the role of the basal ganglia in movement and cognition in 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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.316
Teacher spread0.281 · 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 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

Citations17
Published2001
Admission routes1
Has abstractyes

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