A Low Pulse Food Intake May Contribute to the Poor Nutritional Status and Low Dietary Intakes of Adolescent Girls in Rural Southern Ethiopia
Bibliographic record
Abstract
Poor nutrition in adolescent girls poses critical health risks on future pregnancy and birth outcomes especially in developing countries. Our purpose was to assess nutritional status and dietary intake of rural adolescent girls and determine pulse and food intake patterns associated with poor nutritional status. A cross-sectional community-based study was conducted in a traditional pulse growing region of southern Ethiopia on 188 girls between 15 to 19 years of age, with 70% being from food insecure families. Prevalence of stunting (30.9%) and underweight (13.3%) were associated with low food and nutrient intake. Diets were cereal-based, with both animal source foods and pulses rarely consumed. Improving dietary intakes of female adolescents with nutrient dense foods would ensure better health for themselves and for the next generation.
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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 | 0.000 | 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 | 0.000 | 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".