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Record W2016940452 · doi:10.1080/08035250500281814

Does inadequate maternal iron or DHA status have a negative impact on an infant's functional outcomes?

2005· review· en· W2016940452 on OpenAlexaff
France M. Rioux, Gunilla Lindmark, Olle Hernell

Bibliographic record

VenueActa Paediatrica · 2005
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsMedicinePregnancyIron statusIron deficiencyProspective cohort studyAnimal studiesPhysiologyPediatricsEndocrinologyInternal medicineAnemia

Abstract

fetched live from OpenAlex

UNLABELLED: Marginal intake of iron and omega-3 long-chain fatty acids (DHA) is prevalent among pregnant women. It is not clear to what extent poor iron or DHA status during pregnancy impacts on an infant's functional outcomes. A few studies suggest that inadequate maternal iron or DHA status may be associated with suboptimal functional outcomes in infants. In addition, there is a lack of prospective studies using randomized, double-blind design or experimental studies with appropriate animal models. Although both nutrients are involved in early brain development and their metabolism is interrelated, no study has examined the interaction between iron and omega-3 fatty acids during pregnancy. CONCLUSION: Long-term studies on large cohorts of pregnant women and their infants are needed to determine whether inadequate iron or DHA status during pregnancy is detrimental to infant neurodevelopment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.055
GPT teacher head0.395
Teacher spread0.339 · 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; both teacher heads agree on what is shown here.

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

Citations23
Published2005
Admission routes1
Has abstractyes

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