Impact of sustainable diets on micronutrient intakes and status: outcomes of the MyPlanetDiet randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Data from dietary intervention studies to test the ability of sustainable diets to meet micronutrient (MN) requirements is required. OBJECTIVES: To compare MN intakes and status among adults who received dietary counseling to follow a sustainable diet or a standard healthy diet. METHODS: We conducted a single-blind, randomized controlled trial among 355 healthy adults aged 18‒64 y in 3 centers over 12-wk. Participants received personalized dietary counseling; the intervention arm for a sustainable healthy diet, and the control arm for a healthy diet. Greenhouse gas emissions (GHGEs), MNs, and biomarkers of nutritional status were assessed, and the prevalence of inadequate intakes was defined by the proportion of participants with usual intakes below harmonized average requirements. Data were analyzed using a 2-way mixed analysis of covariance (time and treatment) on complete cases. RESULTS: status did not change. CONCLUSIONS: A diet based on sustainable dietary principles lowered dietary GHGE and several MNs, despite the provision of daily servings of dairy, 3 weekly servings of animal protein, and 2 servings of fish. These findings show that MNs should be considered in developing environmentally protective diets. This trial was registered at clinicaltrials.gov as NCT05253547.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".