Integrated multi-trophic aquaculture with the California sea cucumber (parastichopus californicus): investigating grow-out cage design for juvenile sea cucumbers co-cultured with Pacific oysters (crassostrea gigas)
Bibliographic record
Abstract
Excess nutrients in the form of uneaten food or waste from intensive, monospecies aquaculture farms can have negative effects on the surrounding natural ecosystem, causing eutrophication and benthic habitat degradation. Biomitigative techniques such as Integrated Multi-Trophic Aquaculture (IMTA) are being investigated for their ability to reduce these negative environmental impacts. IMTA is the co-culture of multiple species from complementary trophic levels, physically orientated in such a way that excess waste nutrients from the fed component are intercepted by the extractive species. For IMTA systems to become a sustainable aquaculture design alternative, it is important to ensure that infrastructure orientation and stocking densities of the extractive species maximize the amount of excess nutrients intercepted and overall system efficiency. Previous research has shown that the majority of wastes from fed finfish are made up of large organic particulates which sink rapidly to the benthos underneath or near the fish cages and which would be available to benthic deposit-feeding species. The California sea cucumber (Parastichopus californicus) is a promising extractive species for IMTA on the west coast of Canada due to its deposit-feeding behaviour and its relatively high market price. Owing to the sea cucumber’s morphology and ability to move through restricted spaces, containment can be difficult without reducing nutrient transfer and overall IMTA system efficiency (i.e. mesh sizes needed to contain small sea cucumbers may restrict flow of farm particulates to them). The overall goal of the present work is to effectively contain juvenile sea cucumbers in such a way that maximizes benthic extraction of large-particulate nutrients within an IMTA 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".