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Record W4414789688 · doi:10.1038/s41390-025-04448-5

Magnetic resonance imaging and spectroscopy in neonatal encephalopathy: current consensus position and future opportunities

2025· article· en· W4414789688 on OpenAlexaff
Abbot R. Laptook, Aisling A. Garvey, Caroline Adams, P. Ellen Grant, Eleanor J. Molloy, Lauren C. Weeke, Manon J.N.L. Benders, Misun Hwang, Mohamed El‐Dib, Nadia Badawi, Nicola J. Robertson, Raymand Pang, Sudhin Thayyil, Terrie E. Inder, Ted Carl Kejlberg Andelius, Kasper Jacobsen Kyng, Akihisa Okumura, Arastoo Vossough, Caroline Vande Walle, Donna M. Ferriero, Kirsten A. Donald, Linda S. de Vries, Mai‐Lan Ho, Michelle Machie, Niek van der Aa, Petra S. Hüppi, Pia Wintermark, Sarah Lee, Sara Reis Teixeira, Sonika Agarwal, Sylke J. Steggerda, Vann Chau, Xiaoxi Chen

Bibliographic record

VenuePediatric Research · 2025
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsMcGill UniversityUniversity of TorontoMontreal Children's HospitalHospital for Sick ChildrenTrinity College
Fundersnot available
KeywordsMagnetic resonance imagingNeonatal encephalopathyNeuroimagingGold standard (test)In vivo magnetic resonance spectroscopyDiffusion MRIEncephalopathyFunctional magnetic resonance imaging

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)0.044
metaresearch head score (Gemma)0.041
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: Review · Consensus signal: Review
Teacher disagreement score0.044
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0040.004
Science and technology studies0.0010.005
Scholarly communication0.0080.013
Open science0.0040.003
Research integrity0.0100.008
Insufficient payload (model declined to judge)0.0050.002

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 head0.032
GPT teacher head0.346
Teacher spread0.314 · 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
GenreReview

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

Citations3
Published2025
Admission routes1
Has abstractno

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