Commercial Performance of Blue Mussel (Mytilus edulis, L.) Stocks at a Microgeographic Scale
Bibliographic record
Abstract
Bivalve aquaculture is an important component of the economy in eastern Canada. Because of current social, environmental, economic, and resource constraints, offshore mussel cultivation seems to be a promising strategy. With the objective of optimizing farming strategies that support the sustainability and development of the mussel industry at a microgeographic scale, we evaluated, after a traditional two year production cycle, the commercial performance of spat from several mussel (Mytilus edulis) stocks originating from sites separated by less than 65 km and cultivated at two different grow-out sites (shallow lagoon and offshore waters). The spatiotemporal variation in spat performance was studied through a multiyear in situ “stock-site” spat transfer design. The spat supply originating from the Bassin du Havre-Aubert lagoon systematically exhibited a larger size at sleeving time when compared to other stocks, and a better productivity level when harvested. Nevertheless, an alternative strategy would be to collect spat from the Havre-aux-Maisons lagoon, mostly because of the important commercial volumes of spat that can be collected there. Commercial performance (net income) was three times higher in the deep offshore grow-out site than in the shallow lagoon site. This better productivity in the open sea confirms the highly valuable strategy of offshore mussel farming in this area, where it was hypothesized that the less stressful environmental conditions positively influence reproduction, survival, and growth trends.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".