Bibliographic record
Abstract
Filter-feeding bivalves represent a significant area of aquaculture development and are widely recognized for their valuable ecosystem services. They are considered extractive species, capable of capturing excess nutrients from the environment and converting them into nutritious food for human consumption. Triploidy has been widely used in the oyster industry to enhance production, as triploid oysters allocate most of their energy toward growth. However, the reported productivity gains remain contentious, with some studies indicating that triploidy confers no significant advantage or disadvantage. This approach could also be applied to other shellfish species to boost productivity and improve other energy-dependent processes, such as byssogenesis in mussels. Mussels are one of the most extensively cultivated shellfish species globally and play a significant economic role in coastal regions of Canada. A major challenge in suspension-cultured mussel farming is the high rate of mussel fall-off from cultivation ropes, which reduces harvest yields. Additionally, mussel detachment affects the ecosystem services provided by these filter-feeding organisms in coastal habitats. Mussels remain attached in suspension culture through byssal thread production, a crucial attachment mechanism. Weak byssal thread attachment is a key factor contributing to detachment, and various environmental and biological factors influence this process. This review explores advancements in shellfish productivity through the use of triploidy and examines how this management strategy could be leveraged to enhance byssal attachment capacity in mussels.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".