Management of fish farm sludge in vertical flow treatment wetlands planted with macrophytes: mesocosm experiment
Bibliographic record
Abstract
Inland fish farms are significant sources of water pollution. The main objectives of this work were to: a) develop on-site methods for fish farm sludge management and treatment with modified partly hydraulically saturated vertical flow treatment wetlands (TWs); b) to determine if effective TWs’ plant species, Phragmites australis subsp. australis (invasive in North America), could be replaced with native Phragmites australis subsp. americanus. The performance of 12 on-site mesocosms (both species and unplanted mesocosms in 4 replicates) during two vegetation periods was assessed. The TWs were fed with a batch load of raw sludge, influent and effluent quality and plant development were monitored. Good sludge dewatering and percolate treatment was achieved in TWs (solids removal over 80%; COD 50-70%; TKN and TP 50-60%). As there were no significant differences in efficiency of the sub-species and unplanted mesocosms, the native Phragmites could replace the invasive in TWs. Longer lasting full-scale studies should be done to assess the influence of plants and species choice to the TW performance in order to validate the findings of this experiment.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".