MétaCan
Menu
Back to cohort
Record W3139041858 · doi:10.3389/fnins.2021.650082

Robust Cortical Thickness Morphometry of Neonatal Brain and Systematic Evaluation Using Multi-Site MRI Datasets

2021· article· en· W3139041858 on OpenAlexaff
Mengting Liu, Claude Lepage, Sharon Kim, Seun Jeon, Sun Hyung Kim, Julia Pia Simon, Nina Tanaka, Shiyu Yuan, Tasfiya Islam, Bailin Peng, Knarik Arutyunyan, Wesley Surento, Justin Kim, Neda Jahanshad, Martin Styner, Arthur W. Toga, A. James Barkovich, Duan Xu, Alan C. Evans, Hosung Kim

Bibliographic record

VenueFrontiers in Neuroscience · 2021
Typearticle
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute on AgingNational Institutes of HealthNational Institute of Biomedical Imaging and BioengineeringNational Institute of Neurological Disorders and StrokeBrightFocus Foundation
KeywordsVoxelSegmentationComputer scienceArtificial intelligenceMagnetic resonance imagingPattern recognition (psychology)NeuroimagingPipeline (software)Brain morphometryRobustness (evolution)NeuroscienceMedicineBiologyRadiology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.060
GPT teacher head0.305
Teacher spread0.245 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations28
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in NeuroscienceSame topicFetal and Pediatric Neurological DisordersFrench-language works237,207