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Record W3087194435 · doi:10.1038/s41593-020-00709-0

Issues and recommendations from the OHBM COBIDAS MEEG committee for reproducible EEG and MEG research

2020· review· en· W3087194435 on OpenAlexaff
Cyril Pernet, Marta I. Garrido, Alexandre Gramfort, Natasha M. Maurits, Christoph M. Michel, Elizabeth W. Pang, Riitta Salmelin, Jan‐Mathijs Schoffelen, Pedro A. Valdés‐Sosa, Aina Puce

Bibliographic record

VenueNature Neuroscience · 2020
Typereview
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsSickKids Foundation
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsNeuroimagingData sharingMagnetoencephalographyElectroencephalographyNeuroinformaticsBest practiceComputer scienceSet (abstract data type)Data scienceOpen sciencePsychologyNeuroscienceMedicinePolitical science

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)0.220
metaresearch head score (Gemma)0.301
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.780
Threshold uncertainty score0.962

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2200.301
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0050.005
Science and technology studies0.0050.008
Scholarly communication0.0140.011
Open science0.0120.009
Research integrity0.0520.044
Insufficient payload (model declined to judge)0.0170.025

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 head0.225
GPT teacher head0.457
Teacher spread0.232 · 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
DomainReproducibility
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

Citations249
Published2020
Admission routes1
Has abstractno

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