Food and nutrition security in the Hindu Kush Himalayan region
Bibliographic record
Abstract
The status of food and nutrition security and its underlying factors in the Hindu-Kush Himalayan (HKH) region is investigated. In this region, one third to a half of children (<5 years of age) suffer from stunting, with the incidence of wasting and under-weight also being very high. The prevalence of stunting, wasting and under-weight in children is particularly high in some mountain areas such as Meghalaya state in India, the western mountains and far-western hills of Nepal, Balochistan province in Pakistan, eastern Afghanistan, and Chin state in Myanmar. Food habits in the HKH region are changing. This has led to a deterioration in traditional mountain food systems with a decline in agrobiodiversity. Factors such as high poverty and low dietary energy intakes, a lack of hygienic environments, inadequate nutritional knowledge, and climate change and environmental degradation are also influencing food and nutrition security in the HKH region. To achieve sustainable food and nutrition security in the mountains, this study suggests a multi-sectoral integrated approach with consideration of nutritional aspects in all development processes dealing with economic, social, agricultural and public health issues. © 2017 Society of Chemical Industry.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".