Summer temperature regimes in southcentral Alaska streams: watershed drivers of variation and potential implications for Pacific salmon
Bibliographic record
Abstract
Climate is changing fastest in high-latitude regions, focusing our research on understanding rates and drivers of changing temperature regimes in southcentral Alaska streams and implications for salmon populations. We collected continuous water and air temperature data during open-water periods from 2008 to 2012 in 48 nonglacial salmon streams across the Cook Inlet basin spanning a range of watershed characteristics. The most important predictors of maximum temperatures, expressed as mean July temperature, maximum weekly average temperature, and maximum weekly maximum temperature (MWMT), were mean elevation and wetland cover, while thermal sensitivity (slope of the stream–air temperature relationship) was best explained by mean elevation and area. Although maximum stream temperatures varied widely between years and across sites (8.4 to 23.7 °C), MWMT at most sites exceeded established criterion for spawning and incubation (13 °C), above which chronic and sublethal effects become likely, every year of the study, which suggests salmon are already experiencing thermal stress. Projections of MWMT over the next ∼50 years suggest these criteria will be exceeded at more sites and by increasing margins.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".