Determining the upper thermal tolerance of Athabasca Rainbow Trout (<i>Oncorhynchus mykiss</i>) across naturally varying stream temperatures
Bibliographic record
Abstract
Stream temperature is a key driver of physiological function in ectothermic fish, and fish have clear upper and lower limits to thermal habitat use. Stream temperature increases from climate change are a major threat to coldwater taxa like Athabasca Rainbow Trout ( Oncorhynchus mykiss), listed as Endangered under Canada's Species at Risk Act. To better understand their vulnerability to climate change and prioritize recovery locations, Athabasca Rainbow Trout were collected in August 2021 from three streams in the upper Athabasca River, Alberta, Canada, across a gradient of thermal regimes ranging from cold to warm. Individual thermal tolerance was measured using two physiological metrics: agitation temperature ( Tag) and critical thermal maxima (CTmax) using a portable streamside laboratory. Tag is a behavioural indicator of a thermal avoidance threshold, whereas CTmax is a physiological response that can be interpreted as the upper thermal limit where long term survival is reduced. Results provide strong evidence that CTmax is a plastic metric in Athabasca Rainbow Trout; however, Tag is not. This suggests that Athabasca Rainbow Trout demonstrate some thermal plasticity in terms of CTmax, yet the lack of plasticity in Tag indicates potential limitations in their adaptability to warming stream temperatures.
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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) | 0.001 | 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".