The Role of Avocados in Maternal Diets during the Periconceptional Period, Pregnancy, and Lactation
Bibliographic record
Abstract
Maternal nutrition plays a crucial role in influencing fertility, fetal development, birth outcomes, and breast milk composition. During the critical window of time from conception through the initiation of complementary feeding, the nutrition of the mother is the nutrition of the offspring-and a mother's dietary choices can affect both the early health status and lifelong disease risk of the offspring. Most health expert recommendations and government-sponsored dietary guidelines agree that a healthy diet for children and adults (including those who are pregnant and/or lactating) should include an abundance of nutrient-rich foods such as fruits and vegetables. These foods should contain a variety of essential nutrients as well as other compounds that are associated with lower disease risk such as fiber and bioactives. However, the number and amounts of nutrients varies considerably among fruits and vegetables, and not all fruit and vegetable options are considered "nutrient-rich". Avocados are unique among fruits and vegetables in that, by weight, they contain much higher amounts of the key nutrients folate and potassium, which are normally under-consumed in maternal diets. Avocados also contain higher amounts of several non-essential compounds, such as fiber, monounsaturated fats, and lipid-soluble antioxidants, which have all been linked to improvements in maternal health, birth outcomes and/or breast milk quality. The objective of this report is to review the evidence that avocados may be a unique nutrition source for pregnant and lactating women and, thus, should be considered for inclusion in future dietary recommendations for expecting and new mothers.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".