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Record W4388583556 · doi:10.5888/pcd20.230159

Suboptimal Intake of Fruits and Vegetables in Nine Selected Countries of the World Health Organization European Region

2023· article· en· W4388583556 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePreventing Chronic Disease · 2023
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsPublic Health OntarioUniversity of TorontoUniversity of AlbertaSt. Michael's Hospital
FundersWorld Health Organization
KeywordsMedicinePublic healthHealth promotionDiseaseChronic diseaseEnvironmental healthPromotion (chess)Peer reviewFamily medicineGerontologyNursingPathology

Abstract

fetched live from OpenAlex

The objective of this study was to characterize fruit and vegetable consumption in 9 selected countries of the World Health Organization (WHO) European Region. We analyzed data on fruit and vegetable intake and participant sociodemographic characteristics for 30,455 adults in 9 Eastern European and Central Asian countries via standardized STEPS survey methodology. Fruit and vegetable consumption across all countries was suboptimal, with a high percentage of populations not meeting the WHO-recommended intake of at least 5 servings (400 g) per day. Strengthened implementation of evidence-based policies to increase intake of fruit and vegetables is needed to reduce the burden of and disparities in NCDs.

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.

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)0.000
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 score0.006
Threshold uncertainty score0.191

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.268
Teacher spread0.254 · 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