Re-examination of dairy as a single commodity in US dietary guidance
Bibliographic record
Abstract
Dairy products have been a key component of dietary guidance in the United States for more than 100 years. In light of major advances in the understanding of dietary intake and metabolism, the aim of this review was to examine whether dairy should remain a single commodity in federal guidance. Considerations include recognizing that a substantial proportion of the world's adult population (65%-70%) exhibits lactase nonpersistence, a reduced ability to metabolize lactose to glucose and galactose. Shifts in the US population, including a greater proportion of African Americans and Asians, are of key importance because several studies have shown a markedly higher prevalence of lactase nonpersistence and, consequently, a lower dairy intake among these groups. While cow's milk alternatives are available, families who use them will pay up to an additional $1400 per year compared with those who are able to consume dairy products. Dietary guidance also contains downstream effects for government assistance, such as the US Department of Agriculture's National School Lunch Program and School Breakfast Program. For reasons like these, Canada has recently removed dairy as a separate food group in national dietary guidance. The results of the present review suggest that consideration of this modification when developing population-level guidelines in the United States is warranted.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".