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Record W2953806211 · doi:10.82308/39669

The interrelationship among maternal infection, folate and vitamin B12 status, and offspring growth in Indigenous Panamanians

2012· article· en· W2953806211 on OpenAlexfundno aff
Brock A. Williams

Bibliographic record

VenueeScholarship@McGill (McGill) · 2012
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
FundersMcGill University
KeywordsVitamin B12OffspringMicronutrientPopulationPregnancyBiologyPhysiologyMedicineEnvironmental healthEndocrinology

Abstract

fetched live from OpenAlex

The Interrelationship among Maternal Infection, Folate and Vitamin B12 Status, and Offspring Growth in Indigenous Panamanians. In Panama, the rates of vitamin B12 deficiency for Indigenous mothers pre- and post-natal are 85% and 46%, respectively, whereas, the rates of folate deficiency pre- and post-natal are 46% and 31%, respectively. Vitamin B12 and folate status, therefore, are public health concerns in this indigenous population. White blood cell indices and a wide range of infection markers emerged as factors associated with the serum concentrations of these two micronutrients. Although maternal vitamin B12 and folate concentrations did not have an association with fetal growth, maternal diet (consumption of animal source foods and green folate source foods) was positively associated with infant weight-for-age and length-for-age, respectively. Furthermore, maternal physical characteristics (specifically height and cardiac rate) and infections (specifically oral and skin infections) emerged as factors associated with infant growth. These findings suggest that a complex interrelationship between maternal infection, vitamin B12 and folate status, and offspring growth exists within this population.

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 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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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