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Record W2982371600 · doi:10.1093/ajcn/nqz252

Should formula for infants provide arachidonic acid along with DHA? A position paper of the European Academy of Paediatrics and the Child Health Foundation

2019· article· en· W2982371600 on OpenAlexaff
Berthold Koletzko, Karin Bergmann, J. Thomas Brenna, Philip C. Calder, Cristina Campoy, M. T. Clandinin, John Colombo, Mandy Daly, Támas Décsi, Hans Demmelmair, Magnus Domellöf, Nataša Fidler Mis, Inés González-Casanova, Johannes B. van Goudoever, Adamos Hadjipanayis, Olle Hernell, Alexandre Lapillonne, Silke Mader, Camilia R. Martin, Valerie Matthäus, Usha Ramakrishan, Cornelius M. Smuts, JJ Strain, Conny Tanjung, Patrick Tounian, Susan E. Carlson

Bibliographic record

VenueAmerican Journal of Clinical Nutrition · 2019
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of Alberta
FundersEuropean CommissionEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentDanone
KeywordsInfant formulaArachidonic acidEuropean unionMedicineDocosahexaenoic acidPediatricsHuman healthFood scienceChemistryEnvironmental healthFatty acidPolyunsaturated fatty acidBiochemistryBusinessInternational trade

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 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)0.005
metaresearch head score (Gemma)0.001
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 score0.829
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.383
Teacher spread0.347 · 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

Citations130
Published2019
Admission routes1
Has abstractno

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