Decadal changes in Gulf of Alaska upwelling source waters
Bibliographic record
Abstract
Abstract Decadal changes in sea surface temperature (SST) in the Gulf of Alaska are linked to long‐term transitions in the marine ecosystem. While previous studies have identified the atmospheric variability of the Aleutian Low as an important driver of Ekman pumping and low‐frequency SST anomalies, the role of subsurface gyre‐scale dynamics remains unexplored. Using a set of reanalysis data sets from 1958 to the present, we find that subsurface temperature anomalies generated along the North Pacific Current significantly contribute through mean upwelling to decadal changes of SST in the Gulf of Alaska. This influence is comparable to the contribution associated with variations in atmospheric winds. Given the exceptional low‐frequency character of the propagation of subsurface anomalies (e.g., multidecadal) along the gyre, monitoring subsurface temperature anomalies up stream along the North Pacific Current may enhance the decadal predictability of SST in the Gulf of Alaska and its impact on local marine ecosystems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".