Effect of elevated embryonic incubation temperature on the temperature preference of juvenile lake ( <i>Coregonus clupeaformis</i> ) and round whitefish ( <i>Prosopium cylindraceum</i> )
Bibliographic record
Abstract
Abstract Anthropogenic impacts can lead to increased temperatures in freshwater environments through thermal effluent and climate change. Thermal preference of aquatic organisms can be modulated by abiotic and biotic factors including environmental temperature. Whether increased temperature during embryogenesis can lead to long-term alterations in thermal preference has not been explicitly tested in native freshwater species. Lake (Coregonus clupeaformis) and round (Prosopium cylindraceum) whitefish were incubated at natural and elevated temperatures until hatching, following which, all groups were moved to common garden conditions (15°C) during the post-hatching stage. Temperature preference was determined at 8 months (Lake whitefish only) and 12 months of age (both species) using a shuttle box system. Round whitefish preferred a cooler temperature when incubated at 2 and 6°C compared with 0.5°C. Lake whitefish had similar temperature preferences regardless of age, weight and incubation temperature. These results reveal that temperature preference in freshwater fish can be programmed during early development, and that round whitefish may be more sensitive to incubation temperature. This study highlights the effects that small increases in temperature caused by anthropogenic impacts may have on cold-adapted freshwater fish.
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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 | 0.000 | 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".