The Aquaculture of <i>Porphyra Leucosticta</i> (Rhodophyta) for an Integrated Finfish/Seaweed Recirculating Aquaculture System in an Urban Application
Bibliographic record
Abstract
Abstract Aquaculture represents an excellent opportunity to help rejuvenate blighted coastal urban areas on the north‐east coast. Aquaculture requires relatively little space, often acquired at reduced cost in ungentrified city areas, and can represent an attractive, environmentally benign form of commerce. However, finfish and shellfish aquaculture operations are a source of an effluent with high concentrations of dissolved inorganic nutrients (N, P). To prevent eutrophication, the EPA is developing stringent guidelines for the release of N and P into coastal waters. An integrated recirculating aquaculture system, coupling the growth of seaweed and fish, can solve these problems for urban aquaculture facilities; not only is the effluent remediated but an additional multiproduct, high‐value crop can be generated. One tank‐based (on land) marine aquaculture operation is GreatBay Aquaculture, LLC (Portsmouth, NH), a land‐based hatchery and grow‐out facility for high value summer flounder and cod. Our work is to develop an integrated finfish/seaweed recirculating aquaculture system (RAS) suitable for urban aquaculture. Our RAS system will integrate the culture of summer flounder and native species of seaweed (i.e. Porphyra). BRVAS students are working along side undergraduate and graduate students in the construction and operation of these systems. There are at least seven recognized species of Porphyra in the north‐east. We have begun mesoscale evaluation of P. leucosticta, since it may be a good candidate for the food (sushi) and for r‐phycoerythrin industries. The mass culture techniques (in both free culture and attached to nets) for this Porphyra species are developing. We will report on the mass seeding technologies that we have developed and the specific growth rates of P. leucosticta at the BRVAS culture facilities.
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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".