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Record W4407369727 · doi:10.1038/s41593-025-01900-x

Author Correction: The architecture of the human default mode network explored through cytoarchitecture, wiring and signal flow

2025· erratum· en· W4407369727 on OpenAlexaff
Casey Paquola, Margaret Garber, Stefan Frässle, Jessica Royer, Yigu Zhou, Shahin Tavakol, Raúl Rodríguez‐Cruces, Donna Gift Cabalo, Sofie L. Valk, Simon B. Eickhoff, Daniel S. Margulies, Alan C. Evans, Katrin Amunts, Elizabeth Jefferies, Jonathan Smallwood, Boris C. Bernhardt

Bibliographic record

VenueNature Neuroscience · 2025
Typeerratum
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsQueen's UniversityMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsCytoarchitectureDefault mode networkNeuroscienceSIGNAL (programming language)ArchitectureSignal-flow graphFunctional connectivityCognitive scienceFlow (mathematics)Computer sciencePsychologyPhysicsEngineeringGeographyElectrical engineering

Abstract

fetched live from OpenAlex

In the version of the article initially published, the initial “B.” was missing from Simon B. Eickhoff’s name and has now been added to the HTML and PDF versions of the article.

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)0.003
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.062
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.046
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0620.029

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 head0.009
GPT teacher head0.289
Teacher spread0.280 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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