Effect of acclimation temperature on thermal tolerance between American lobster (<i>Homarus americanus</i>) collected in different lobster fishing areas in Atlantic Canada
Bibliographic record
Abstract
The American lobster fishery is the most economically significant commercial fishery in Atlantic Canada and takes place in waters that are warming due to climate change. Lobster are poikilotherms that tolerate a wide range of seasonal temperatures with an optimal range of 12–18 °C. Lobster in the Canadian Maritimes may be naturally acclimated to a wide range of temperatures and thus, could have a wide range of thermal tolerance that may be distinct across regions. The present study used non-invasive open-source tools to explore differences in thermal tolerance in real time between geographically separated lobster populations from around the Canadian Maritimes. Lobsters were acquired from six lobster fishing areas in the Canadian Maritimes and acclimated to either warm (15 °C) or cold (5 °C) water for two weeks before the onset of thermal trials. Geographic origin was not a significant predictor of estimated thermal maximum, while acclimation temperature was a significant predictor. These results suggest that thermal tolerance is more strongly linked to acclimation temperature than to geographic region.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".