Digestible Nutrients of Nile Tilapia Feed
Bibliographic record
Abstract
The utilization of energetic and protein feeds, highly digestible as well, becomes more and more necessary due to the quality of formulated rations, fish performance and relationship with the environment. Apparent digestibility coefficient (ADC) of dry matter, protein, energy, phosphorus, and amino acids of corn starch, corn, wheat, rice, soybean, and cottonseed meal, corn gluten and fish meal were determined for Nile tilapia. ADC was determined using a reference diet based on albumin, gelatin and corn starch, was used inert indicator chromium III oxide (Cr2O3). Each test diet composed by 70% of reference diet and 30% of the test diet. Feces were collected using mofied Guelph system. ADC values for protein and average ADC of amino acids were as follows: corn 89.76 and 96.43%, rice meal 95.88 and 92.26%, wheat meal 93.54 and 84.41%, fish meal 82.59 and 86.36%, corn gluten 89.82 and 87.98%, soybean meal 94.13 and 91.93%, cotton meal 87.10 and 77.47%, respectively. According to the results of this work, ADC of protein is not a reliable indicator of ADC values of amino acids, even more so for wheat meal, corn, and cotton meal. Among protein feeds, soybean meal was found to have the highest ADC for protein and amino acids, while corn was the energetic feed with the highest ADC (86.15%) for energy.
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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 | 0.000 | 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".