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Record W2324220138 · doi:10.1093/pch/21.3.145

Folate and neural tube defects: The role of supplements and food fortification

2016· article· en· W2324220138 on OpenAlexaboutno aff
Noam Ami, Mark Bernstein, François Boucher, Michael Rieder, Louise Parker

Bibliographic record

VenuePaediatrics & Child Health · 2016
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsnot available
Fundersnot available
KeywordsFood fortificationFolic acidMedicineNeural tubeFortificationGynecologyEnvironmental healthFood scienceBiologyInternal medicine

Abstract

fetched live from OpenAlex

Periconceptional folic acid significantly reduces the risk of neural tube defects. It is difficult to achieve optimal levels of folate by diet alone, even with fortification of flour, especially because flour consumption in Canada is slightly decreasing. Intermittent concerns have been raised concerning possible deleterious effects of folate supplementation, including the masking of symptoms of vitamin B12 deficiency and an association with cancer, especially colorectal cancer. Both concerns have been disproved. The Canadian Paediatric Society endorses the following steps to enhance folate intake in women of child-bearing age: encouraging the consumption of folate-rich foods such as leafy vegetables, increasing the level of folate food fortification, taking a supplement containing folate and B12, and providing free folate supplementation to disadvantaged women of child-bearing age. These recommendations are consistent with those of the Society of Obstetricians and Gynaecologists of Canada.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.200
Threshold uncertainty score0.180

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.017
GPT teacher head0.295
Teacher spread0.278 · 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

Citations59
Published2016
Admission routes1
Has abstractyes

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