Monitoring Sodium Content in Processed Foods in Argentina 2017–2018: Compliance with National Legislation and Regional Targets
Bibliographic record
Abstract
Sodium intake in Argentina has been estimated to be at least double the dose of 2000 mg/day recommended by WHO, mostly coming from processed foods. Argentina is one of the few countries in the world that have regulated sodium content in certain food products. This study presents an assessment of sodium content in a selection of food groups and categories as reported in the nutrient information panels. We surveyed 3674 food products, and the sodium content of 864 and 1375 of them was compared to the maximum levels according to the Argentinean law and the regional targets, respectively. All food categories presented high variability of sodium content. Over 90% of the products included in the national sodium reduction law were found to be compliant. Food groups with high median sodium, such as condiments, sauces and spreads, and fish and fish products, are not included in the national law. In turn, comparisons with the lower regional targets indicated that almost 50% of the products analyzed had sodium contents above the recommended values. This evidence suggests that enhancing sodium reduction in processed foods may be a necessity for public health objectives and it is also technically feasible in Argentina.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".