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Benchmarking functional connectome-based predictive models for resting-state fMRI

2019· article· en· W2890996272 on OpenAlexfundno aff
Kamalaker Dadi, Mehdi Rahim, Alexandre Abraham, Darya Chyzhyk, Milham Michael, Bertrand Thirion, Gaël Varoquaux

Bibliographic record

VenueNeuroImage · 2019
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsnot available
FundersNational Institute on AgingNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchAlzheimer's Disease Neuroimaging InitiativeGE HealthcareGenentechNational Institutes of HealthH. Lundbeck A/SServierEisaiFujirebio EuropeHorizon 2020DoD Alzheimer's Disease Neuroimaging InitiativePfizerBiogenEli Lilly and CompanyU.S. Department of DefenseNovartis Pharmaceuticals CorporationBristol-Myers SquibbAgence Nationale de la RechercheRocheMerckAlzheimer's Drug Discovery FoundationTakeda Pharmaceutical CompanyAbbVieAlzheimer's Association
KeywordsConnectomeResting state fMRIArtificial intelligenceMachine learningComputer scienceHuman Connectome ProjectRegressionBenchmark (surveying)PsychologyFunctional connectivityNeuroscience

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.058
GPT teacher head0.264
Teacher spread0.206 · 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 designSimulation or modeling
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

Citations366
Published2019
Admission routes1
Has abstractno

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