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Record W2786515370 · doi:10.3171/2017.10.focus17609

Transcranial magnetic resonance imaging–guided focused ultrasound thalamotomy for tremor: technical note

2018· article· en· W2786515370 on OpenAlex
Tony R. Wang, A.E. Bond, Robert F. Dallapiazza, Aaron Blanke, David Tilden, Thomas Huerta, Shayan Moosa, Francesco Prada, W. Jeffrey Elias

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

VenueNeurosurgical FOCUS · 2018
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsToronto Western HospitalUniversity Health Network
FundersFocused Ultrasound Foundation
KeywordsThalamotomyFocused ultrasoundEssential tremorMedicineMagnetic resonance imagingNeurosurgeryMedical physicsUltrasoundPhysical medicine and rehabilitationRadiologyParkinson's diseaseDeep brain stimulationDisease

Abstract

fetched live from OpenAlex

Although the use of focused ultrasound (FUS) in neurosurgery dates to the 1950s, its clinical utility was limited by the need for a craniotomy to create an acoustic window. Recent technological advances have enabled efficient transcranial delivery of US. Moreover, US is now coupled with MRI to ensure precise energy delivery and monitoring. Thus, MRI-guided transcranial FUS lesioning is now being investigated for myriad neurological and psychiatric disorders. Among the first transcranial FUS treatments is thalamotomy for the treatment of various tremors. The authors provide a technical overview of FUS thalamotomy for tremor as well as important lessons learned during their experience with this emerging technology.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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