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Record W7132943618

Total Folate and Synthetic Folic Acid Content in the Food Supply and Its Influence on Absorption Across the Colon

2020· dissertation· W7132943618 on OpenAlexfundaboutno aff
Siya Sunita Khanna

Bibliographic record

VenueTSpace · 2020
Typedissertation
Language
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFortificationFolic acidFood fortificationFortified FoodPregnancyAbsorption (acoustics)Folic acid supplementation
DOInot available

Abstract

fetched live from OpenAlex

To reduce the risk of neural tube defect-affected pregnancies in Canada, folic acid fortification of foods is mandated, and women planning a pregnancy are advised to consume a folic acid-containing supplement. This research aims to determine the amount of folic acid in fortified foods and understand the impact of folic acid on folate absorption in the colon. In study one, analysis of fortified foods by microbial analysis and mass spectroscopy showed 65% higher folate values than in the Canadian Nutrient File. In study two, an on-going randomized clinical trial, we seek to investigate the influence of folic acid on folate absorption in the colon. Data herein verify the feasibility of the protocol and that the feeding and supplement intervention produced two distinct groups in terms of blood folate status. This work will facilitate an improved understanding of available sources of folate to inform future folate supplementation and fortification recommendations.

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 score0.081
Threshold uncertainty score0.160

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.363
Teacher spread0.316 · 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
Published2020
Admission routes2
Has abstractyes

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