RED LENTILS BALLS (Red Lentils Balls as A Healthy Food with High Protein and Rich in Fiber)
Bibliographic record
Abstract
Red lentils balls are meatballs that come from vegetarian. This red lentils balls still new in Indonesia. Because the author found fact, Indonesia people never know what is red lentils. Red lentils balls cook quickly and don’t need washed too long in the water. Also, red lentils balls have many nutrition such as vitamin B, fiber, and high in protein. The citizen need know about red lentils balls history. Red lentils are an edible pulse. It is a bushy annual plant of the legume family, known for its lens-shape seeds. It is about 40 cm (16 in) tall, and the seeds grow in pods, usually with two seeds in each. In South Asian cuisine, split lentils (often with their hulls removed) are known as dal. Usually eaten with rice and bread, the lentil is a dietary staple throughout regions of India, Sri Lanka, Pakistan, Bangladesh, and Nepal. As a food crop, the majority of world production comes from Canada, India, and Australia. Red lentils are known to be rich in protein, so it is ranked third in protein content by weight of all types of nuts, after soybeans and hemp. The proteins contained include the essential amino acids of isoleucine and lysine. Lentils are a cheap source of protein, Lentils do not contain two essential amino acids, namely methionine and cysteine. Lentils are a good source of iron, capable of providing more than an adult's daily needs in just one cup.
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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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
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".