The physiological state of four commercially important bivalve species during a naturally occurring heatwave
Bibliographic record
Abstract
Shallow coastal environments are becoming more susceptible to marine heatwaves, particularly in Atlantic Canada, which is experiencing higher rates of ocean warming compared with the global average. Understanding bivalves’ tolerance to heatwaves in Atlantic Canada is especially important, given the magnitude of bivalve aquaculture in this region. In this study, the physiological state of four commercially important bivalve species—blue mussel ( Mytilus edulis Linnaeus, 1758), eastern oyster ( Crassostrea virginica (Gmelin, 1791)), soft shell clam ( Mya arenaria Linnaeus, 1758), and hard clam ( Mercenaria mercenaria (Linnaeus, 1758))—was observed during a naturally occurring heatwave in Prince Edward Island, Canada. The metabolism, feeding physiology, and scope for growth of each species were compared. Results from this study, and comparisons with the literature, show interspecific variability in the metabolic rate and feeding physiology between species, but generally oysters, soft shell clams, and hard clams were less impacted during the heatwave compared with the blue mussels. Additionally, only the scope for growth of mussels declined throughout this experiment, which may be explained by cumulative heat stress, as temperatures experienced during this heatwave exceeded the thermal tolerance limits of 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 | 0.001 | 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) | 0.000 | 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 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".