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Record W4283768444 · doi:10.1016/j.brs.2022.06.013

Pulse width modulation-based TMS: Primary motor cortex responses compared to conventional monophasic stimuli

2022· letter· en· W4283768444 on OpenAlexaboutno aff
Majid Memarian Sorkhabi, Karen Wendt, Jacinta O’Shea, Timothy Denison

Bibliographic record

VenueBrain stimulation · 2022
Typeletter
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsnot available
FundersMedical Research CouncilUniversity of OxfordRoyal SocietyRoyal Academy of EngineeringWellcome Trust
KeywordsPrimary motor cortexMotor cortexModulation (music)NeuroscienceMedicineMaterials sciencePsychologyPhysicsStimulationAcoustics

Abstract

fetched live from OpenAlex

Transcranial magnetic stimulation (TMS) is a non-invasive method of stimulating and modulating the nervous system. Most TMS devices are limited to predefined pulse shapes, such as monophasic or biphasic cosine-shaped pulses. Recently, the use of state-of-the-art power electronic instruments has permitted more control over the waveform parameters in several newer devices [1,2] (for a review of recent advances see supplementary file). A technique using pulse width modulation (PWM), called programmable TMS or pTMS, enables the approximation of a wide range of arbitrary pulses [3,4].

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0120.001

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 head0.054
GPT teacher head0.307
Teacher spread0.253 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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