RELEVANCE OF A RAPID APPRAISAL APPROACH TO IDENTIFY LOCALLY AVAILABLE FEED INGREDIENTS TO SMALL-SCALE NILE TILAPIA ( <i>Oreochromis niloticus</i> L.) AQUACULTURE
Bibliographic record
Abstract
Applications of a rapid appraisal approach to identify locally available feed ingredients in feed formulation, production, and socio-economics of Nile tilapia aquaculture in Bangladesh are discussed. Three diets of 35%, 30%, and 25% crude protein were formulated using locally available ingredients, and their essential amino acid profiles were assessed for Nile tilapia. Six production scenarios were constructed using these diets and two culture periods of 100 and 150 days were considered. The production scenarios with 35% protein yielded the highest productivity and profitability over the 150-day culture period followed by the 30% protein scenario. Identification of locally available ingredients and their application in small-scale Nile tilapia aquaculture may lead to: (1) increased availability of inexpensive sources of fish production for poor people; (2) increased fish consumption; (3) increased self employment and involvement of women in productive activities; and (4) increased household income to reduce poverty.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".