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Record W3042754439 · doi:10.1016/j.brs.2020.07.005

Phase-dependent transcranial magnetic stimulation of the lesioned hemisphere is accurate after stroke

2020· letter· en· W3042754439 on OpenAlexfundno aff
Sara J. Hussain, William Hayward, Farah Fourcand, Christoph Zrenner, Ulf Ziemann, Ethan R. Buch, Margaret K. Hayward, Leonardo G. Cohen

Bibliographic record

VenueBrain stimulation · 2020
Typeletter
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeBristol-Myers Squibb CanadaNational Cancer InstituteEuropean Research CouncilU.S. Department of Health and Human ServicesNational Institutes of HealthBundesministerium für Bildung und FrauenBundesministerium für Bildung und ForschungDeutsche Forschungsgemeinschaft
KeywordsTranscranial magnetic stimulationStroke (engine)NeuroscienceStimulationPhysical medicine and rehabilitationMedicineBrain stimulationPsychologyPhysics

Abstract

fetched live from OpenAlex

Transcranial magnetic stimulation (TMS) can produce plastic changes within descending motor pathways and distributed brain networks [1,2]. It has been proposed that TMS could enhance post-stroke motor recovery by normalizing imbalanced sensorimotor network function and/or upregulating corticospinal output [3,4] but studies using TMS to boost motor recovery have shown heterogeneous results [5]. However, TMS has traditionally been delivered uncoupled from endogenous brain oscillatory activity, leading to indiscriminate application of individual TMS pulses across different, physiologically distinct brain states.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.044
GPT teacher head0.292
Teacher spread0.248 · 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 designObservational
Domainnot available
GenreCommentary

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

Citations25
Published2020
Admission routes1
Has abstractyes

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