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Record W2012443162 · doi:10.1002/mds.10149

Deep brain stimulation for Parkinson's disease: Patient selection and evaluation

2002· review· en· W2012443162 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

VenueMovement Disorders · 2002
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsDeep brain stimulationParkinson's diseaseMedicineSelection (genetic algorithm)DiseaseDegenerative diseaseBrain stimulationPhysical medicine and rehabilitationIntensive care medicinePsychological interventionPhysical therapyStimulationPsychiatryComputer sciencePathologyInternal medicineMachine learning

Abstract

fetched live from OpenAlex

Critical to the successful application of deep brain stimulation for the treatment Parkinson's disease is the proper selection of patients who will reliably benefit from this procedure and the successful evaluation of the responses obtained. This review will discuss the various factors influencing patient selection and summarize the recommended approach to patient assessment by using the Core Assessment Program for Surgical Interventions and Transplantation in Parkinson's Disease (CAPSIT-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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
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 integrity0.0000.000
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 head0.046
GPT teacher head0.337
Teacher spread0.291 · 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