Use of green sea urchins (Stroglocentrotus droebachiensis) as a biocontrol for fouling on aquaculture net pens in British Columbia
Bibliographic record
Abstract
Biofouling in the aquaculture industry is an expensive problem, requiring toxic chemical treatments and manual cleaning. It is a problem that negatively impacts fish by occluding net openings, thereby reducing water flow and stressing stocks, as well as physically damaging nets. However, many invertebrates feed on and remove sessile fouling organisms from substrata. Biocontrol aims to add these natural grazers to aquaculture systems to control fouling. Ideally the biocontrol is also exploited so that the method becomes a form of polyculture. This study aims to determine the feasibility of using green sea urchins (Strongylocentrotus droebachiensis) as a biocontrol in sablefish net pens. The experiment involved immersing sample nets at several depths with varying urchin densities. The efficacy of urchins as biocontrols was measured using dry-weight, and remote sensing techniques were used to determine percent net occlusion. The results will be used to determine optimal carrying capacity, as well as minimum and maximum densities for the use of green sea urchins as biocontrols on net pens at commercial scales.
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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 | 0.001 | 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".