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Record W4414334988 · doi:10.3390/nu17182987

The Relationship Between Regulatory Frameworks for Protein Content Claims for Plant Protein Foods and the Nutrient Intakes of Canadian Adults

2025· article· en· W4414334988 on OpenAlexafffundabout
Songhee Back, Christopher P. F. Marinangeli, Antonio Rossi, Lamar Elfaki, Mavra Ahmed, Victoria Chen, Shuting Yang, Andreea Zurbau, Alison M. Duncan, Mary R. L’Abbé, Cyril W.C. Kendall, John L. Sievenpiper, Laura Chiavaroli

Bibliographic record

VenueNutrients · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsUniversity of SaskatchewanUniversity of TorontoGlycemic Index LaboratoriesThe Wilson CentreUniversity of GuelphSt. Michael's Hospital
FundersPulse CanadaCanadian Institutes of Health ResearchUniversity of TorontoGovernment of CanadaUniversities Space Research AssociationLoblaw Companies Limited
KeywordsNutrientPlant proteinEuropean unionProtein qualityFood groupServing sizeFood productsMember statesFood insecurity

Abstract

fetched live from OpenAlex

Background: The inability to assign a protein content claim (PCC) to plant foods may impede efforts from Canada’s Food Guide to increase consumption of plant protein. A systematic application of PCC frameworks from other regions to Canadian nutrition surveillance data would be useful to model potential effects of PCC regulations on the nutrient intake, protein quality, and corrected protein intake of diets. Methods: Plant food groups that qualified for a PCC within the Canadian Nutrient File according to regulations from Canada, the United States (US), Australia and New Zealand (ANZ), and the European Union (EU) were identified. Adults (≥19 years) (n = 11,817) from The Canadian Community Health Survey (2015) who consumed ≥1 plant food qualifying for a PCC in each region were allocated to the corresponding PCC group. The effects of Canadian PCC regulations on the protein quantity, quality (Digestible Indispensable Amino Acid Score, DIAAS), and nutrient intakes of Canadian diets in adults were compared to PCC groups from other regions. Results: Substantially more individuals were consumers of plant-based protein foods, using the ANZ and the EU PCC regulations, compared to the Canadian and US PCC groups. There were no differences in uncorrected protein intake across PCC groups. All DIAAS values were >0.94, and corrected protein intakes were >74–89 g/day or 16%E across PCC groups. Non-consumers of plant foods eligible for a PCC had corrected protein intakes that ranged between 68 and 78 g/d or 17%E. Generally, consumers of plant foods eligible for a PCC in the US, ANZ, and EU, or both Canada and the US/ANZ/EU, had higher intakes of positive nutrients, such as fibre, calcium, iron, magnesium, and zinc (p < 0.05) and lower saturated fat. Conclusions: Less restrictive regulatory frameworks for PCC used in ANZ and the EU did not substantially affect protein intake or the protein quality of Canadian diets in adults. These results suggest that more inclusive regulatory frameworks for protein PCCs could support increased intake of food sources of plant proteins in alignment with Canada’s Food Guide.

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)0.003
metaresearch head score (Gemma)0.012
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 score0.027
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.228
Teacher spread0.209 · 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

Citations2
Published2025
Admission routes3
Has abstractyes

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