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Record W3096550593 · doi:10.1002/advs.202002026

Transcranial Ultrasound Innovations Ready for Broad Clinical Application

2020· review· en· W3096550593 on OpenAlex
Roland Beisteiner, Andrés M. Lozano

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

VenueAdvanced Science · 2020
Typereview
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversity of Toronto
FundersMedizinische Universität WienUniversität Wien
KeywordsMedicineAgeing societyFocused ultrasoundBrain stimulationNeuroscienceDeep brain stimulationBlood–brain barrierIntensive care medicineUltrasoundPathologyStimulationRadiologyInternal medicineCentral nervous systemDiseasePsychology

Abstract

fetched live from OpenAlex

Brain diseases are one of the most important problems in our rapidly ageing society. Currently, there are not many effective medications and surgical options are limited due to invasiveness and non-invasive brain stimulation techniques cannot be well targeted and cannot access deep brain areas. A novel therapy is transcranial ultrasound which allows a variety of treatments without opening of the skull. Recent technological developments generated three revolutionary options including 1) targeted non-invasive surgery, 2) highly targeted drug, antibody, or gene therapy via local opening of the blood-brain barrier, and 3) highly targeted brain stimulation to improve pathological brain functions. This progress report summarizes the current state of the art for clinical application and the results of recent patient investigations.

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 score0.998
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
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.065
GPT teacher head0.389
Teacher spread0.324 · 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