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Record W2258254301 · doi:10.1038/pr.2016.11

Early postnatal docosahexaenoic acid levels and improved preterm brain development

2016· article· en· W2258254301 on OpenAlexafffund
Emily Tam, Vann Chau, A. James Barkovich, Donna M. Ferriero, Steven P. Miller, Elizabeth E. Rogers, Ruth E. Grunau, Anne Synnes, Duan Xu, Justin Foong, Rollin Brant, Sheila M. Innis

Bibliographic record

VenuePediatric Research · 2016
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of British ColumbiaHospital for Sick ChildrenUniversity of TorontoSickKids Foundation
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentUniversity of British ColumbiaNational Institute of Biomedical Imaging and BioengineeringNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsIntraventricular hemorrhageDocosahexaenoic acidMedicineGestational agePolyunsaturated fatty acidWhite matterConfoundingBayley Scales of Infant DevelopmentMagnetic resonance imagingOdds ratioBrain developmentPediatricsPhysiologyInternal medicineFatty acidPregnancyPsychomotor learningBiologyBiochemistryRadiology

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.072
GPT teacher head0.378
Teacher spread0.306 · 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 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

Citations97
Published2016
Admission routes2
Has abstractno

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