87 Algal bioremediation of eutrophic effluents in small scale integrated aquaculture systems
Bibliographic record
Abstract
Non‐point source eutrophication of coastal waters is a significant problem that may be exacerbated locally by effluent from aquaculture operations. Porphyra spp. grow and assimilate nutrients rapidly, making them good candidates for eutrophication abatement via systems of integrated aquaculture. I summarize our work examining the bioremediatory performance (growth rate, nutrient assimilation, tissue N and pigment content) of four U.S. and three Asian Porphyra species as functions of N concentration and source (nitrate vs. ammonium). The Northeast U.S. species P. amplissima is the best performing local bioremediator (maximum growth rate and tissue N=24% d‐1, 5.2% DW, respectively), comparing well with P. yezoensis, an economically important species in Asia. When tissue remained non‐reproductive, P. amplissima growing in 300 μM ammonium removed 99–100% of N but only about 50% of P (fed 10:1 molar N:P ratio). We have begun investigating the relationship between stocking density and yield, and will begin demonstration scale tests of the mesoscale system.
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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".