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Record W2984032218 · doi:10.1093/brain/awaa009

Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)

2020· article· en· W2984032218 on OpenAlexaff
Tomas Ros, Stefanie Enriquez‐Geppert, Vadim Zotev, Kymberly D. Young, Guilherme Wood, Susan Whitfield‐Gabrieli, Feng Wan, Patrik Vuilleumier, François Vialatte, Dimitri Van De Ville, Doron Todder, Tanju Sürmeli, James Sulzer, Ute Strehl, M. B. Sterman, Naomi J. Steiner, Bettina Sorger, Surjo R. Soekadar, Ranganatha Sitaram, Leslie Sherlin, Michael Schönenberg, Frank Scharnowski, Manuel Schabus, Katya Rubia, Agostinho Rosa, Miriam Reiner, Jaime A. Pineda, Christian Paret, Alexei Ossadtchi, Andrew A. Nicholson, Wenya Nan, Javier Mínguez, Jean‐Arthur Micoulaud‐Franchi, David M. A. Mehler, Michael Lührs, Joel F. Lubar, Fabien Lotte, David E.J. Linden, Jarrod A. Lewis‐Peacock, Mikhail Lebedev, Ruth A. Lanius, Andrea Kübler, Cornelia Kranczioch, Yury Koush, Lilian Konicar, Simon H. Kohl, Silivia E Kober, Manousos A. Klados, Camille Jeunet, Tieme W. P. Janssen, René J. Huster, Kerstin Hoedlmoser, Laurence Hirshberg, Stephan Heunis, Talma Hendler, Michelle Hampson, Adrian G. Guggisberg, Robert Guggenberger, John Gruzelier, Rainer W Göbel, Nicolas Gninenko, Alireza Gharabaghi, Paul Frewen, Thomas Fovet, Thalı́a Fernández, Carlos Escolano, Ann‐Christine Ehlis, Renate Drechsler, R. Christopher deCharms, Stefan Debener, Dirk De Ridder, Eddy J. Davelaar, Marco Congedo, Marc Cavazza, M.H.M. Breteler, Daniel Brandeis, Jerzy Bodurka, Niels Birbaumer, Olga Bazanova, Beatrix Barth, Panagiotis D. Bamidis, Tibor Auer, Martijn Arns, Robert T. Thibault

Bibliographic record

VenueBrain · 2020
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsWestern University
FundersMedical Research CouncilNational Research University Higher School of EconomicsNational Center for Advancing Translational SciencesNational Eye InstituteAction Medical Research
KeywordsNeurofeedbackScrutinyChecklistMainstreamPsychologyCognitionApplied psychologyClinical psychologyMedicinePsychiatryCognitive psychologyPolitical science

Abstract

fetched live from OpenAlex

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

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)0.592
metaresearch head score (Gemma)0.676
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.408
Threshold uncertainty score0.504

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5920.676
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.008
Bibliometrics0.0110.007
Science and technology studies0.0060.008
Scholarly communication0.0070.004
Open science0.0110.009
Research integrity0.0120.012
Insufficient payload (model declined to judge)0.0030.003

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 head0.329
GPT teacher head0.427
Teacher spread0.098 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReporting
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

Citations396
Published2020
Admission routes1
Has abstractyes

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