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Record W4322011961 · doi:10.1016/j.cdnut.2023.100059

A Cross-Sectional Analysis of Products Marketed as Plant-Based Across the United States, United Kingdom, and Canada Using Online Nutrition Information

2023· article· en· W4322011961 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCurrent Developments in Nutrition · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsQueen's UniversityMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMealFood scienceBusinessFood productsAgricultural scienceAdvertisingBiology

Abstract

fetched live from OpenAlex

The food industry is responding to a rising demand for plant-based foods by developing and marketing an ever-wider range of vegan and vegetarian products under the banner of “plant-based.” Understanding the nutritional properties of these products is critical. To assess the number, meal type, and nutritional content of products marketed as plant-based (MaPB) from the perspective of the consumer across multiple sectors in the United States, United Kingdom, and Canada. An online search for products MaPB was performed across supermarkets, restaurants, food manufacturers, and plant-based meal delivery companies in the United Kingdom, the United States, and Canada using the terms: “vegan,” “vegetarian,” and “plant-based.” Online nutrition data were extracted, and whole meals that comprised >50% of ingredients such as fruits, vegetables, legumes, nuts, and seeds were identified. The nutritional content of dishes MaPB in restaurants was also directly compared with meat-containing dishes. Further, 3488 unique products were identified, of which 962 were whole meals and 1137 were a replacement for the main protein component in a meal, including 771 meat alternatives. Across all sectors, 45% of whole meals had >15-g protein, 70% had <10% kcal from saturated fat; 29% had >10-g fiber per meal, and 86% had <1000 mg sodium. At restaurants, 1507 meat-containing dishes were identified and compared with 191 vegetarian and 81 vegan dishes. The meat-containing dishes were higher in protein [35.4 g (24.0–51.4)] compared with vegetarian [19.0 g (13.0–26.1)] and vegan [16.2 g (10.5–23.2) dishes (P < 0.001)]. The vegan dishes were low in saturated fat and sodium (SFA: 6.3 g ± 6.4, Sodium: 800 mg (545.0–1410.0) compared with both meat [SFA: 11.6 g ± 10.0; Sodium: 1280 mg (820.0–1952.0)] and vegetarian [SFA: 9.4 g ± 7.6; Sodium: 1011 mg (603.0–1560.0)] options (P < 0.001 for all comparisons). Products MaPB tend to have lower concentrations of saturated fat and sodium than their meat-containing counterparts, but improvements are needed to optimize their nutritional composition.

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 score0.097
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
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 head0.030
GPT teacher head0.300
Teacher spread0.270 · 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