Photographic Methods for Measuring Packaged Food and Beverage Products in Supermarkets
Why this work is in the frame
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Bibliographic record
Abstract
The global obesity pandemic and rates of nutrition-related noncommunicable diseases (NCDs) have increased worldwide, especially in the Latin American and Caribbean region. In an attempt to control this obesity epidemic, the Chilean government has established a comprehensive set of regulatory actions, including beverage taxation, warning labels on foods, and marketing restrictions to children. To improve the effectiveness of actions to prevent obesity, a better understanding of the food environment is needed. We developed and standardized photographic methods to assess and monitor packaged food and beverage products in supermarkets. A standardized protocol and food categorization system was used to guide photo collection and data management of photos taken between February and April 2015 in 11 supermarkets, consisting of 5 different supermarket chains, from high- (n = 6) and lower-middle (n = 5)-income neighborhoods in Santiago, Chile. Photos (n = ∼50,000) from nearly 10,000 unique food products from high- and lower-middle-income neighborhoods were used for this study. We developed standardized methods to use photographs to assess and monitor the food environment. A food categorization scheme is essential to guiding the data collection process. Substantial time and human resources are required to assess packaged food and beverage products in supermarkets. Because the number of photos per food product is variable, the organization of the photographs according to the food categorization system, before data entry, is imperative for easy access during data entry and analysis. We identified the information necessary for a photographic registry, which, with the food categorization system, is critical to create unique identifiers that are linked to each food product and its photos. To adequately monitor food environments, standardized methods for food photo collection and management are essential. The information collected on food package photos to monitor food environments is important for guiding and evaluating actions in the context of the ongoing obesity and NCD epidemics.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it