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Record W2984265948 · doi:10.3390/nu11112738

Nutritional Content According to the Presence of Front of Package Marketing Strategies: The Case of Ultra-Processed Snack Food Products Purchased in Costa Rica

2019· article· en· W2984265948 on OpenAlexfundno aff
Tatiana Gamboa-Gamboa, Adriana Blanco‐Metzler, Stefanie Vandevijvere, Manuel Ramírez‐Zea, María F Kroker-Lobos

Bibliographic record

VenueNutrients · 2019
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsNutrition facts labelFood marketingBusinessHealth claims on food labelsFood productsMarketingHypermarketNutrition informationFood scienceSnack foodFood processingEnvironmental healthAdvertisingMedicineBiology

Abstract

fetched live from OpenAlex

The industry uses nutrition and health claims, premium offers, and promotional characters as marketing strategies (MS). The inclusion of these MS on ultra-processed products may influence child and adolescent purchase behavior. This study determined the proportion of foods carrying claims and marketing strategies, also the proportion of products with critical nutrients declaration, and nutritional profile differences between products that carry or not claims and MS on the front-of-package (FoP) of ultra-processed food products sold in Costa Rica. Data were obtained from 2423 photographs of seven food groups consumed as snacks that were sold in one of the most widespread and popular hypermarket chains in Costa Rica in 2015. Ten percent of products lacked a nutrition facts panel. Sodium was the least reported critical nutrient. Energy and critical nutrients were significantly highest in products that did not include any nutrition or health claim and in products that included at least one MS. Forty-four percent and 10% of all products displayed at least one nutrition or at least one health claim, respectively, and 23% displayed at least one MS. In conclusion, regulations are needed to restrict claims and marketing on ultra-processed food packages to generate healthier food environments and contribute to the prevention of childhood and adolescent obesity in Costa Rica.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.038
GPT teacher head0.282
Teacher spread0.244 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations30
Published2019
Admission routes1
Has abstractyes

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