Pulse Phytonutrients: Nutritional and Medicinal Importance
Bibliographic record
Abstract
Pulses are important food crops which offer significant nutritional and health advantages due to their high protein content and a unique nutritional profile, i.e., low fat source of digestible protein, dietary fibre, complex carbohydrates, resistant starch and a number of essential vitamins, especially, the B-group vitamin B9 (folate). In addition to these vitamins and minerals contributing to a healthy diet, pulses contain a number of non-nutritive bioactive substances including enzyme inhibitors, lectins, saponins, phytates, phenolic compounds and oligosaccharides. The latter contributes beyond basic nutritional value and is particularly helpful in the fight against non-communicable diseases often associated with diet transitions and rising incomes. Phytic acid exhibits antioxidant activity and protects DNA damage, phenolic compounds have antioxidant and other important physiological and biological properties, and galacto-oligosaccharides may elicit prebiotic activity. Research findings on different phytochemicals in pulse seeds and their role in preventing the lifestyle diseases has been discussed. Encouraging awareness of the nutritional value of pulses can help consumers adopt healthier diets and also could be an important dietary factor in improving longevity.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".