Variation in the Proximate, Energy and Mineral Compositions of Different Body Parts of Macrobrachium macrobranchion (Prawn)
Bibliographic record
Abstract
The proximate and elemental compositions of various body parts of Macrobrachium macrobranchion (prawn) obtained from the Great Kwa River, a major tributary of Cross River estuary in Cross River State, Nigeria were investigated using standard methods of AOAC. Results showed that the flesh had significantly higher (p < 0.05) levels of protein, fat and moisture (22.32, 7.70 and 58.40%, respectively) than the other body parts analyzed. Equally high in protein were the head (20.11%) and appendages (19.28%), while the exoskeleton recorded the least protein content (14.02%). The flesh had the least (p < 0.05) crude fibre (0.03%) and carbohydrate (7.22%) contents, and conversely had the least energy value (187.50 kcal/g) among the body parts. Ash content was significantly higher (p < 0.05) in the exoskeleton (7.14%), the appendages (7.01%) and the head (6.05%) than in the flesh (4.30%). Individual elements were also unequally distributed among the four body parts investigated: sodium and potassium were more concentrated in the flesh (189.27 mg/100 g and 114.70 mg/100 g, respectively), while calcium and magnesium were highest in the appendages (99.02 mg/100 g and 171.40 mg/100 g, respectively). The concentration of iron was generally low among the body parts; however, it was highest (p < 0.05) in the head. The usual practice of retaining the flesh and discarding the “hard” parts (head, exoskeleton and appendages) of prawn during food preparation should be discouraged as this may promote wastage of important nutrients.
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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 | 0.000 |
| 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) | 0.001 | 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".