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Gradients in brain organization

2022· editorial· en· W4211239355 on OpenAlexafffund
Boris C. Bernhardt, Jonathan Smallwood, Shella Keilholz, Daniel S. Margulies

Bibliographic record

VenueNeuroImage · 2022
Typeeditorial
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsQueen's UniversityMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute of Neurological Disorders and StrokeHorizon 2020National Institute of Biomedical Imaging and BioengineeringEuropean Research CouncilNatural Sciences and Engineering Research Council of CanadaCentre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de MontréalNational Institute of Mental HealthHospital for Sick ChildrenCentre National de la Recherche ScientifiqueNational Institutes of HealthQueen's UniversityCanada Research ChairsInstitute of Musculoskeletal Health and ArthritisMcGill UniversityEmory UniversityCanadian Institutes of Health ResearchNational Science FoundationUniversité de ParisEuropean CommissionGeorgia Institute of Technology
KeywordsNeurosciencePsychology

Abstract

fetched live from OpenAlex

International audience

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)0.007
metaresearch head score (Gemma)0.027
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.026
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.027
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0050.002
Science and technology studies0.0030.004
Scholarly communication0.0090.005
Open science0.0030.003
Research integrity0.0260.026
Insufficient payload (model declined to judge)0.0230.013

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 head0.020
GPT teacher head0.264
Teacher spread0.244 · 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
GenreEditorial

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

Citations144
Published2022
Admission routes2
Has abstractyes

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