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Guidelines for reporting an fMRI study

2008· article· en· W2117981173 on OpenAlexaff
Russell A. Poldrack, Paul C. Fletcher, Richard N. Henson, Keith J. Worsley, Matthew Brett, Thomas E. Nichols

Bibliographic record

VenueNeuroImage · 2008
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsMcGill University
FundersWellcome Trust
KeywordsChecklistFunctional magnetic resonance imagingSet (abstract data type)Medical physicsMagnetic resonance imagingPsychologyComputer scienceMedicineNeuroscienceCognitive psychologyRadiology

Abstract

fetched live from OpenAlex

In this editorial, we outline a set of guidelines for the reporting of methods and results in functional magnetic resonance imaging studies and provide a checklist to assist authors in preparing manuscripts that meet these guidelines.

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)0.193
metaresearch head score (Gemma)0.512
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.807
Threshold uncertainty score0.995

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1930.512
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0210.009
Science and technology studies0.0040.005
Scholarly communication0.0090.006
Open science0.0080.003
Research integrity0.0120.015
Insufficient payload (model declined to judge)0.0290.043

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 head0.411
GPT teacher head0.420
Teacher spread0.009 · 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
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

Citations563
Published2008
Admission routes1
Has abstractyes

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