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Record W3111318509 · doi:10.1016/j.clinph.2020.11.018

Training in the practice of noninvasive brain stimulation: Recommendations from an IFCN committee

2020· review· en· W3111318509 on OpenAlexaff
Peter J. Fried, Emiliano Santarnecchi, Andrea Antal, David Bartrés‐Faz, Sven Bestmann, Linda L. Carpenter, Pablo Celnik, Dylan J. Edwards, Faranak Farzan, Shirley Fecteau, Mark S. George, Bin He, Yun‐Hee Kim, Letizia Leocani, Sarah H. Lisanby, Colleen Loo, Bruce Luber, Michael A. Nitsche, Walter Paulus, Símone Rossi, Paolo Maria Rossini, John C. Rothwell, Alexander T. Sack, Gregor Thut, Yoshikazu Ugawa, Ulf Ziemann, Mark Hallett, Álvaro Pascual‐Leone

Bibliographic record

VenueClinical Neurophysiology · 2020
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsUniversité LavalSimon Fraser University
FundersNational Institute of General Medical SciencesBeth Israel Deaconess Medical Center
KeywordsBrain stimulationMedical educationPsychologyMedicineEngineering ethicsNeuroscienceStimulationEngineering

Abstract

fetched live from OpenAlex

As the field of noninvasive brain stimulation (NIBS) expands, there is a growing need for comprehensive guidelines on training practitioners in the safe and effective administration of NIBS techniques in their various research and clinical applications. This article provides recommendations on the structure and content of this training. Three different types of practitioners are considered (Technicians, Clinicians, and Scientists), to attempt to cover the range of education and responsibilities of practitioners in NIBS from the laboratory to the clinic. Basic or core competencies and more advanced knowledge and skills are discussed, and recommendations offered regarding didactic and practical curricular components. We encourage individual licensing and governing bodies to implement these guidelines.

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 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)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.309
GPT teacher head0.489
Teacher spread0.180 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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

Citations92
Published2020
Admission routes1
Has abstractyes

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