The Australian Food and Health Dialogue – the implications of the sodium recommendation for pasta sauces
Bibliographic record
Abstract
OBJECTIVE: To assess the change in Na content of Australian pasta sauces between 2008 and 2011. A secondary objective was to project the mean Na content of these same products in 2014 using the Australian Food and Health Dialogue Na commitment and compare projections with the 2012 UK Na target for pasta sauce. DESIGN: Na data were collected from the product labels of pasta sauce products. Mean Na content was calculated for 2008 and 2011 and change assessed. Projected mean values for 2014 were derived by applying a 15 % reduction to the 2011 products above the 'action point' of 420 mg Na/100 g, consistent with the Food and Health Dialogue commitment (scenario 1). A 15 % reduction was applied to products already below the 'action point' (scenario 2). Projections were compared with the 2012 UK target. SETTING: Na data for pasta sauce products in Australian supermarkets (July-September) in 2008 and 2011. SUBJECTS: Not applicable. RESULTS: Data were available for 124 (2008) and 187 (2011) products, and mean Na levels were not significantly different (451 mg/100 g v. 423 mg/100 g; P = 0·16). The projected means (381 mg Na/100 g in scenario 1; 375 mg Na/100 g in scenario 2) exceeded the 2012 UK target (330 mg Na/100 g) and to attain this would require a 22 % reduction from 2011 levels. CONCLUSIONS: There is little evidence that all Australian manufacturers of pasta sauces systematically reduced the Na content of their products between 2008 and 2011. Even if all manufacturers achieve the current voluntary commitment by 2014, average salt levels in Australian products would still be above the 2012 UK target.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".