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Record W3151254714 · doi:10.1111/ene.14851

Emerging concepts on bradykinesia in non‐parkinsonian conditions

2021· review· en· W3151254714 on OpenAlexaff
Giulia Paparella, Alfonso Fasano, Mark Hallett, Alfredo Berardelli, Matteo Bologna

Bibliographic record

VenueEuropean Journal of Neurology · 2021
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsOntario Brain InstituteToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsParkinsonismDystoniaMovement disordersNeuroscienceHypokinesiaMotor symptomsPhysical medicine and rehabilitationMedicineContext (archaeology)ChoreaParkinson's diseaseDementiaPsychologyDiseasePathology

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Bradykinesia is one of the cardinal motor symptoms of Parkinson's disease. However, clinical and experimental studies indicate that bradykinesia may also be observed in various neurological diseases not primarily characterized by parkinsonism. These conditions include hyperkinetic movement disorders, such as dystonia, chorea, and essential tremor. Bradykinesia may also be observed in patients with neurological conditions that are not seen as "movement disorders," including those characterized by the involvement of the cerebellum and corticospinal system, dementia, multiple sclerosis, and psychiatric disorders. METHODS: We reviewed clinical reports and experimental studies on bradykinesia in non-parkinsonian conditions and discussed the major findings. RESULTS: Bradykinesia is a common motor abnormality in non-parkinsonian conditions. From a pathophysiological standpoint, bradykinesia in neurological conditions not primarily characterized by parkinsonism may be explained by brain network dysfunction. CONCLUSION: In addition to the pathophysiological implications, the present paper highlights important terminological issues and the need for a new, more accurate, and more widely used definition of bradykinesia in the context of movement disorders and other neurological conditions.

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 score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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 head0.049
GPT teacher head0.372
Teacher spread0.322 · 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

Citations47
Published2021
Admission routes1
Has abstractyes

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