Identification of raw materials that can be used in fish farming in feed manufacturing industries in Senegal
Bibliographic record
Abstract
This study is part of a process aimed at enhancing the value of local raw materials used in animal feed manufacturing companies in Senegal and likely to be used in fish feed in aquaculture. The study was carried out in four (4) geographical areas of Senegal (North, South, Centre-West, East), specifically among thirteen (13) active companies. The results of the survey show that 100% of the companies source certain raw materials on the local market. However, the percentage of imported raw materials represents 30.8% of the inputs used in the food manufacturing process. Sixty-one point five percent (61.5%) of companies obtain their raw materials at less than 500 FCFA/kg. The purchase prices of these food inputs and the food production of the companies vary respectively on average between 501 and 750 FCFA/kg, and between 40 and 50 tonnes/year. This food production is intended for livestock, poultry and farmed fish.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".