Modeling of waste outputs in the aquatic environment from a commercial cage farm under neotropical climate conditions
Why this work is in the frame
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Bibliographic record
Abstract
The present study used a bioenergetics modeling approach to estimate the solid and dissolved waste outputs of a Nile tilapia Oreochromis niloticus net-cage farm. Historical production data for 30 cages were obtained from a commercial farm in the Chavantes Reservoir, São Paulo State, Brazil. In addition, an experiment was carried out in 4 net-cages at the farm to validate this dataset and collect fish samples. A total of 32400 tilapias with an initial weight averaging 35 ± 2.73 g were equally distributed in the experimental net cages. After 210 d, the fish showed a final individual weight of ~789 ± 5.12 g. Fish growth performance was monitored, and body composition was analyzed each month. Digestibility trials of commercial diets used for juvenile stages JVI and JVII and market weight were performed. Relationships of body weight with body content data of water, protein, fat, ash, gross energy, phosphorus, and nitrogen were evaluated by regression analysis. The total digestible energy requirement and estimated residues of the fish were assessed using the factorial bioenergetics model, adapted to the growing conditions of a neotropical reservoir. The model estimated ~320 kg of total solid waste released per tonne of tilapia, including ~10 kg of solid nitrogen and ~5 kg of solid phosphorus. Approximately 3 and 47 kg of dissolved phosphorus and nitrogen, respectively, were estimated per tonne of tilapia. The bioenergetics model is a valuable and equitable method for assessing and monitoring waste outputs. It can improve the nutritional and environmental efficiency of aquaculture activities, helping producers to reduce feed costs while strengthening the environmental sustainability of aquaculture.
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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 | 0.000 | 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 | 0.001 |
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 it