MétaCan
Menu
Back to cohort
Record W2891144030 · doi:10.1007/s11682-018-9941-x

A resting state fMRI analysis pipeline for pooling inference across diverse cohorts: an ENIGMA rs-fMRI protocol

2018· review· en· W2891144030 on OpenAlexaff
Bhim M. Adhikari, Neda Jahanshad, D. K. Shukla, Jessica A. Turner, Dominik Grotegerd, Udo Dannlowski, Harald Kugel, Jennifer Engelen, Bruno Dietsche, Axel Krug, Tilo Kircher, Els Fieremans, Jelle Veraart, Dmitry S. Novikov, Premika S.W. Boedhoe, Ysbrand D. van der Werf, Odile A. van den Heuvel, Jonathan Ipser, Anne Uhlmann, Dan J. Stein, Erin W. Dickie, Aristotle N. Voineskos, Anil K. Malhotra, Fabrizio Pizzagalli, Vince D. Calhoun, Lea Waller, Ilja M. Veer, Robert W. Buchanan, David C. Glahn, L. Elliot Hong, Paul M. Thompson, Peter Kochunov

Bibliographic record

VenueBrain Imaging and Behavior · 2018
Typereview
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute on Drug AbuseNational Institutes of HealthFonds Wetenschappelijk OnderzoekNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthVlaamse regeringDeutsche Forschungsgemeinschaft
KeywordsResting state fMRIComputer sciencePoolingProtocol (science)NeuroimagingStatistical powerArtificial intelligenceData qualityFalse discovery ratePattern recognition (psychology)Missing dataData miningMachine learningStatisticsPsychologyNeuroscienceMedicineMathematics

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)0.007
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0220.011

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 head0.121
GPT teacher head0.433
Teacher spread0.312 · 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
GenreProtocol

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

Citations61
Published2018
Admission routes1
Has abstractno

Explore more

Same venueBrain Imaging and BehaviorSame topicFunctional Brain Connectivity StudiesFrench-language works237,207