Dietary guidance on plant-based meat alternatives for individuals wanting to increase plant protein intake
Bibliographic record
Abstract
A new generation of plant-based meat alternatives (PBMAs) has entered the mainstream. These products contain concentrated sources of plant protein and are formulated to mimic the taste and texture of their meat-based counterparts, especially red meat. The increased availability of these products coincides with calls from health agencies to increase the dietary plant-to-animal protein ratio for health and environmental reasons. The role of PBMAs in achieving the goal of consuming more plant protein may be particularly important since consumption of whole plant foods, such as legumes, which includes pulses (e.g., beans, peas and lentils), is unlikely to increase without major public policy initiatives. Nevertheless, there is debate about the healthfulness of PBMAs and about whether the benefits associated with traditional plant-based diets emphasizing whole plant foods apply to PBMAs. These products are heavily processed, often high in sodium, and contain lower levels of compounds (e.g., fiber, resistant starch, polyphenols) typically associated with the benefits of plant-based diets. On the other hand, PBMAs are excellent sources of protein, and many are fortified with nutrients of concern in plant-based diets. Collectively, the evidence suggests that while they may not provide all the benefits of whole legumes, PBMAs have health and environmental advantages over comparable animal-derived foods. For most individuals, a daily serving of a PBMA fits well within the context of an overall healthy diet. Higher intakes may also be compatible with healthy eating, especially for those whose protein and/or calorie needs are increased.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".