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Record W4220698326 · doi:10.1038/s41596-021-00664-5

A checklist for assessing the methodological quality of concurrent tES-fMRI studies (ContES checklist): a consensus study and statement

2022· review· en· W4220698326 on OpenAlexafffund
Hamed Ekhtiari, Peyman Ghobadi‐Azbari, Axel Thielscher, Andrea Antal, Lucia M. Li, A. Duke Shereen, Yuranny Cabral‐Calderín, Daniel Keeser, Til Ole Bergmann, Asif Jamil, Inês R. Violante, Jorge Almeida, Marcus Meinzer, Hartwig R. Siebner, Adam J. Woods, Charlotte J. Stagg, Rany Abend, Daria Antonenko, Tibor Auer, Marc Bächinger, Chris Baeken, Helen C. Barron, Henry W. Chase, Jenny Crinion, Abhishek Datta, Matthew H. Davis, Mohsen Ebrahimi, Zeinab Esmaeilpour, Brian Falcone, Valentina Fiori, Iman Ghodratitoostani, Gadi Gilam, Roland H. Grabner, Joel D. Greenspan, Georg Groen, Gesa Hartwigsen, Tobias U. Hauser, Christoph S. Herrmann, Chi‐Hung Juan, Bart Krekelberg, Stéphanie Lefebvre, Sook‐Lei Liew, Kristoffer H. Madsen, Rasoul Khayati, Nastaran Malmir, Paola Marangolo, Andrew Martin, Timothy J. Meeker, Hossein Mohaddes Ardabili, Marius Moisa, Davide Momi, Beni Mulyana, Alexander Opitz, Natasza Orlov, Patrick Ragert, Christian C. Ruff, Giulio Ruffini, Michaela Ruttorf, Arshiya Sangchooli, Klaus Schellhorn, Gottfried Schlaug, Bernhard Sehm, Ghazaleh Soleimani, Hosna Tavakoli, Benjamin Thompson, Dagmar Timmann, Aki Tsuchiyagaito, Ulrich Martin, Johannes Vosskuhl, Christiane Anne Weinrich, Mehran Zare-Bidoky, Xiaochu Zhang, Benedikt Zoefel, Michael A. Nitsche, Marom Bikson

Bibliographic record

VenueNature Protocols · 2022
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsUniversity of WaterlooCentre for Addiction and Mental Health
FundersNational Institute on Drug AbuseNational Institute of Mental HealthNeuroscience Center Zurich, University of ZurichCentro de Ciências Matemáticas Aplicadas à IndústriaFundação para a Ciência e a TecnologiaLeibniz-GemeinschaftBiotechnology and Biological Sciences Research CouncilQueen Elisabeth Medical FoundationNational Institutes of HealthFondation Médicale Reine ElisabethUniversity of SurreyMinistry of Science and Technology, TaiwanVrije Universiteit BrusselUniversity College LondonLundbeckfondenLaureate Institute for Brain Research, University of TulsaTechnische Universiteit EindhovenMinistero della SaluteCanadian Institutes of Health ResearchFonds Wetenschappelijk OnderzoekEidgenössische Technische Hochschule ZürichBoehringer Ingelheim StiftungLudwig-Maximilians-Universität MünchenVlaamse regeringNational Institute for Health and Care ResearchDeutsche ForschungsgemeinschaftGentofte HospitalEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentChongqing Science and Technology CommissionJohns Hopkins UniversitySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungEberhard Karls Universität TübingenUniversidade de CoimbraJacobs FoundationUniversidade de São PauloEuropean CommissionFundação de Amparo à Pesquisa do Estado de São PauloDeutscher Akademischer AustauschdienstNiedersächsisches Ministerium für Wissenschaft und KulturOklahoma Center for the Advancement of Science and TechnologyUniversity of OxfordNational Institute of Neurological Disorders and StrokeUniversität ZürichNatural Sciences and Engineering Research Council of CanadaBundesministerium für Bildung und ForschungUniversity of QueenslandDivision of Mathematical SciencesWellcome TrustLeibniz-Institut für Arbeitsforschung an der TU DortmundH. Lundbeck A/SMedical Research CouncilMcKnight FoundationNational Institute of General Medical SciencesNational Alliance for Research on Schizophrenia and DepressionUniversity of PittsburghBispebjerg HospitalNational Science FoundationFaculty of Health and Medical Sciences, University of Western AustraliaMax-Planck-GesellschaftRoyal Society
KeywordsChecklistPsychologyDelphi methodDelphiMedicineComputer scienceArtificial intelligenceCognitive psychology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.257
metaresearch head score (Gemma)0.340
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.743
Threshold uncertainty score0.916

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2570.340
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0090.017
Bibliometrics0.0220.011
Science and technology studies0.0050.005
Scholarly communication0.0060.005
Open science0.0100.009
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0110.004

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 head0.677
GPT teacher head0.629
Teacher spread0.048 · 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 designTheoretical or conceptual
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

Citations56
Published2022
Admission routes2
Has abstractno

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