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Record W4414491218 · doi:10.1016/j.neuron.2025.08.026

Reproducible Brain Charts: An open data resource for mapping brain development and its associations with mental health

2025· article· en· W4414491218 on OpenAlexfundno aff
Golia Shafiei, Nathália Bianchini Esper, Maurício Scopel Hoffmann, Lei Ai, Andrew A. Chen, Jon Cluce, Sydney Covitz, Steven Giavasis, Connor Lane, Kahini Mehta, Tyler M. Moore, Taylor Salo, Tinashe M. Tapera, Monica E. Calkins, Stanley J. Colcombe, Christos Davatzikos, Raquel E. Gur, Ruben C. Gur, Pedro Mário Pan, Andrea Parolin Jackowski, Ariel Rokem, Luís Augusto Rohde, Russell T. Shinohara, Nim Tottenham, Xi‐Nian Zuo, Matthew Cieslak, Alexandre R. Franco, Gregory Kiar, Giovanni Abrahão Salum, Michael P. Milham, Theodore D. Satterthwaite

Bibliographic record

VenueNeuron · 2025
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeSpecial Project for Research and Development in Key areas of Guangdong ProvinceCanadian Institutes of Health ResearchNational Institutes of HealthNational Institute of Biomedical Imaging and BioengineeringEuropean Research CouncilBeijing Municipal Science and Technology CommissionNational Social Science Fund of ChinaNederlandse Organisatie voor Wetenschappelijk OnderzoekBeijing Normal UniversityKey Research Program of Frontier Science, Chinese Academy of SciencesConselho Nacional de Desenvolvimento Científico e TecnológicoNational Natural Science Foundation of ChinaNational Key Research and Development Program of ChinaSeventh Framework ProgrammeFundação de Amparo à Pesquisa do Estado de São PauloNational Institute of Mental HealthPfizerEuropean CommissionChinese Academy of Sciences
KeywordsNeuroimagingResource (disambiguation)Mental healthBrain developmentHarmonizationOpen dataData quality

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 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)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.362
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.172
GPT teacher head0.364
Teacher spread0.193 · 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 designNot applicable
Domainnot available
GenreEmpirical

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

Citations7
Published2025
Admission routes1
Has abstractno

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