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Record W2783651254 · doi:10.1159/000481106

Current and Expected Advances in Deep Brain Stimulation for Movement Disorders

2018· review· en· W2783651254 on OpenAlexaff
Ausaf Bari, Jasmine A. Thum, Diana Babayan, Andrés M. Lozano

Bibliographic record

VenueProgress in neurological surgery · 2018
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsDeep brain stimulationMedicineMovement disordersEssential tremorDystoniaPhysical medicine and rehabilitationParkinson's diseaseNeuroscienceDiseasePsychiatryPsychologyPathology

Abstract

fetched live from OpenAlex

Deep brain stimulation (DBS) has become an established treatment for medically refractory movement disorders including Parkinson's disease, essential tremor, and dystonia. The field of DBS continues to evolve with advances in patient selection, target identification, electrode and pulse generator technology, and the development of more effective stimulation paradigms such as closed-loop stimulation. Furthermore, as the safety and efficacy of DBS improves through better hardware design and deeper understanding of its mechanisms of action, the indications for DBS will continue to expand to cover a wider range of disorders. Finally, the recent approval of MR-guided focused ultrasound for the treatment of essential tremor and potentially other movement disorders heralds a resurgence in lesion creation as a viable alternative to DBS for selected patients.

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 score0.820
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 integrity0.0000.000
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 head0.061
GPT teacher head0.381
Teacher spread0.320 · 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

Citations21
Published2018
Admission routes1
Has abstractyes

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