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Record W2064461807 · doi:10.3390/nu2080805

A Food Frequency Questionnaire for the Assessment of Calcium, Vitamin D and Vitamin K: A Pilot Validation Study

2010· article· en· W2064461807 on OpenAlexaff
Janet M. Pritchard, Tinasha Seechurn, Stephanie A. Atkinson

Bibliographic record

VenueNutrients · 2010
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsMcMaster University
FundersU.S. Department of Agriculture
KeywordsVitamin D and neurologyMedicineFood frequency questionnaireQuartileVitaminCalciumOverweightPhysiologyInternal medicineObesity

Abstract

fetched live from OpenAlex

The study objective was to validate a food frequency questionnaire (FFQ) to assess calcium, vitamin D and vitamin K intakes in overweight and obese postmenopausal community-dwelling women. The FFQ was validated against intakes derived from a 5-day diet record (5DDR) that also included assessment of supplement intake. Strong correlations between methods were observed for all nutrients (r = 0.63, 0.89, 0.54 for calcium, vitamin D and vitamin K, respectively) and cross-classification analyses demonstrated no major misclassification of participants into intake quartiles. Bland-Altman analysis showed that the FFQ overestimated intakes for calcium, by 576 mg/day (95% CI, -668 to 1,821 mg/day), for vitamin D by 75 IU/day (95% CI, -359 to 510 IU/day), and for vitamin K by 167 mcg/day (95% CI, -233 to 568 mcg/day). This pilot study showed promising validation evidence for the use of this FFQ, which focuses on calcium, vitamin D and vitamin K intakes in postmenopausal women, as a screening tool in clinical and research settings.

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)0.010
metaresearch head score (Gemma)0.008
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 score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.035
GPT teacher head0.338
Teacher spread0.303 · 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

Citations67
Published2010
Admission routes1
Has abstractyes

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