Climate Change and Pacific Salmon Productivity on the Russian Far East
Bibliographic record
Abstract
Climate change impact is a mainstream topic in Pacific salmon stock dynamics research. Numerous studies analyze correlations of some salmon species or stock abundance conditions with one or another climate index. Meanwhile, it is evident that no one factor impacts salmon or their environment separately from other elements of the salmon ecosystem. To understand the importance of the contributions of the main physical elements into changing environmental conditions of salmon ecosystems in the North Pacific Ocean, we tried to evaluate correlations between commercial catches of several salmon species with the most popular climate indices. These indices characterize large-scale meteorological, oceanographic, and cosmo-physical processes defining the Earth's climate. Climate change impacts on Pacific salmon (pink, chum, and sockeye) productivity was assessed based on long-term fisheries statistics and dynamics of 18 climate indices using stepwise multivariate regression analysis. Three regional stock groups were analyzed: Eastern Kamchatka and Chukotka (BPG), Western Kamchatka and continental coast (NOG), and Sakhalin, Kuriles, Amur River, and Primorye (SOG).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".