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Record W2071882565 · doi:10.1097/wco.0b013e32833b6019

Imaging of compensatory mechanisms in Parkinson's disease

2010· review· en· W2071882565 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Opinion in Neurology · 2010
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsUniversity of British ColumbiaCanadian Sport Centre Pacific
Fundersnot available
KeywordsNeuroscienceDopaminergicBasal gangliaParkinson's diseaseDiseaseMedicinePsychologyDopamineCentral nervous systemPathology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The on-going quest for potentially disease-modifying therapies in Parkinson's disease has prompted the development of methods that can differentiate direct disease effects from compensatory processes. RECENT FINDINGS: PET studies have suggested a number of changes at the synaptic level to maintain integrity of dopaminergic systems. Functional MRI studies support the long-held belief that relatively intact cerebellar circuits may compensate for impaired basal ganglia function. Altered connectivity and increased spatial extent of activation also appear to be mechanisms through which motor and cognitive performance can be maintained. SUMMARY: Ascertaining which changes in brain activation in Parkinson's disease are, in fact, compensatory represents a serious challenge. Compensatory mechanisms have been demonstrated from the microscopic, synaptic level to the macroscopic, system level. Augmentation of compensatory mechanisms, in addition to ameliorating the loss of dopaminergic neurons, may represent a joint strategy for overall minimization of disability.

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.

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 score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.078
GPT teacher head0.379
Teacher spread0.301 · 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