Potentialites Nutritionnelles et Dietetiques des Chenilles Et Insectes Consommes en Rd Congo. Cas de Fruit de Mer, Cirina Forda, Imbrasia Ertli, Ruspolia Differens et Augosoma Centaurus
Bibliographic record
Abstract
Objective: This research entitled "Nutritional and dietary potential of caterpillars and insects consumed in the DRC; case of seafood, Cirina forda, Imbrasia Ertli, Ruspolia dif]ferens and Augosoma centaurus" aims to promote and popularize the consumption of this category of food, because they compete with meat and fish in terms of protein and lipid content and also fruits and vegetables in terms of richness in vitamins and minerals. Finally, the aim is to make available the scientific data necessary for nutrition and dietetics. Methodology: We will conduct a bibliographic search to establish a state of the issue, define the objective, identify the originality and plan this study. Then, we will purchase and collect samples of caterpillars consumed in the DRC; we will carry out chemical analyses including humidity, total ash, crude proteins, lipids, total carbohydrates and mineral elements which were measured using the ICP 8300. Observation: we were able to say that the edible caterpillars analyzed are energetic ranging from 303 (Ruspolia Differens) to 493Kcal/g for Imbrasia Ertli, and represent an important source of proteins (ranging from 50.79 Ruspolia differens to 70.3 Augosoma centaurus). By their richness in Mg [ranging from 288.8 (Imbrasia Ertli) to 1476 mg/Kg (Augosoma Centaurus)]; In Ca [ranging from 202.7 (Imbrasia Ertli) to 950.8 mg/Kg for Fruit de Mer]; The caterpillars respectively have a preventive action against cancer and play a very active role in bone formation. Caterpillars have a curative power against arrhythmia and heart failure due to their richness in Ca, Mg, K and low fat content including in ascending order Ruspolia differens, Augosoma centaurus. They are remineralizing due to their richness in Mg of which the best is Augosoma centaurus; in Ca of which the best is seafood. They are anti-anemic due to their richness in Fe of which the best is Cirina Forda; in proteins of which the best is Imbrasia Ertli and in vitamins of group B (Vit. B12). Recommendation: the rational food consumption of caterpillars and insects in the same way as other foods is recommended and particularly in case of protein-energy malnutrition.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".