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Record W3004863197 · doi:10.1016/j.brs.2020.02.003

A new, open-source 3D-printed transcranial magnetic stimulation (TMS) coil tracker holder for double blind, sham-controlled neuronavigation studies

2020· letter· en· W3004863197 on OpenAlexaboutno aff
Kevin A. Caulfield, James W. Lopez, Claire Cox, Donna R. Roberts, Lisa M. McTeague

Bibliographic record

VenueBrain stimulation · 2020
Typeletter
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of General Medical SciencesU.S. Department of Veterans AffairsNational Aeronautics and Space Administration
KeywordsTranscranial magnetic stimulationNeuronavigationElectromagnetic coilNeuromodulationStimulationPhospheneMedicineBiomedical engineeringNeurosciencePsychologyPhysicsMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

Transcranial magnetic stimulation (TMS) is a form of noninvasive neuromodulation that can be combined with neuronavigation to target specific brain regions and/or ensure reliable application to a given brain region. Current neuronavigation systems use a coil tracker holder that attaches around the handle of a TMS coil, and a coil tracker that inserts into the slot of the coil tracker holder (Fig. 1A). This commercially available TMS coil tracker holder design is one-sided, meaning it contains a slot for a coil tracker holder on only one side.

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)0.002
metaresearch head score (Gemma)0.003
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: Methods · Consensus signal: Methods
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.005

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 head0.132
GPT teacher head0.357
Teacher spread0.224 · 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
GenreMethods

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

Citations3
Published2020
Admission routes1
Has abstractyes

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