Climate change impacts on oyster aquaculture - Part I: Identification of key factors
Bibliographic record
Abstract
Oysters are enriched with high-quality protein and are widely known for their exquisite taste. The production of oysters plays an important role in the local economies of coastal communities in many countries, including Atlantic Canada, because of their high economic value. However, because of the changing climatic conditions in recent years, oyster aquaculture faces potentially negative impacts, such as increasing water acidification, rising water temperatures, high salinity, invasive species, algal blooms, and other environmental factors. Although a few isolated effects of climate change on oyster aquaculture have been reported in recent years, it is not well understood how climate change will affect oyster aquaculture from a systematic perspective. In the first part of this study, we present a systematic review of the impacts of climate change and some key environmental factors affecting oyster production on a global scale. The study also identifies knowledge gaps and challenges. In addition, we present key research directions that will facilitate future investigations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.011 |
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; both teacher heads agree on what is shown here.
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".