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Record W2300102626 · doi:10.1017/cjn.2016.22

Deep Brain Stimulation Target Selection for Parkinson’s Disease

2016· review· en· W2300102626 on OpenAlexaffvenueabout
Christopher R. Honey, Clement Hamani, Suneil K. Kalia, Tejas Sankar, Marina Picillo, Renato P. Munhoz, Alfonso Fasano, Michel Panisset

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2016
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsHôpital Notre-DameToronto Western HospitalUniversité de MontréalUniversity of AlbertaUniversity Health NetworkUniversity of TorontoUniversity of Alberta HospitalCentre for Addiction and Mental HealthHealth Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsDeep brain stimulationSubthalamic nucleusPedunculopontine nucleusParkinson's diseaseNeuroscienceMedicinePhysical medicine and rehabilitationMotor symptomsGlobus pallidusPsychologyBasal gangliaDiseaseCentral nervous systemInternal medicine

Abstract

fetched live from OpenAlex

During the "DBS Canada Day" symposium held in Toronto July 4-5, 2014, the scientific committee invited experts to discuss three main questions on target selection for deep brain stimulation (DBS) of patients with Parkinson's disease (PD). First, is the subthalamic nucleus (STN) or the globus pallidus internus (GPi) the ideal target? In summary, both targets are equally effective in improving the motor symptoms of PD. STN allows a greater medications reduction, while GPi exerts a direct antidyskinetic effect. Second, are there further potential targets? Ventral intermediate nucleus DBS has significant long-term benefit for tremor control but insufficiently addresses other motor features of PD. DBS in the posterior subthalamic area also reduces tremor. The pedunculopontine nucleus remains an investigational target. Third, should DBS for PD be performed unilaterally, bilaterally or staged? Unilateral STN DBS can be proposed to asymmetric patients. There is no evidence that a staged bilateral approach reduces the incidence of DBS-related adverse events.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.055
GPT teacher head0.331
Teacher spread0.275 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations42
Published2016
Admission routes3
Has abstractyes

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