Forcing mechanisms controlling surface and subsurface temperature anomalies along line‐p, North‐East Pacific Ocean
Bibliographic record
Abstract
The influence of different mechanisms on surface and subsurface temperature anomalies is considered along Line‐P, an oceanographic line extending from Vancouver Island into the Gulf of Alaska, which has been sampled for almost half a century. The role of a given mechanism is determined by applying canonical correlation analysis (CCA) between the anomalies of a parameter representing the mechanism and the Line‐P temperature anomalies. For each mechanism, it is determined if its direct influence can be detected, and if so, the domain of Line‐P over which it acts. Two areas along Line‐P, characterized by different forcing mechanisms, are identified: (1) offshore, west of 130°W, the main mechanisms influencing Line‐P temperature anomalies are the Ekman transport due to wind stress anomalies (with the zonal wind stress component somewhat more important than the meridional component) and wind mixing anomalies, (2) from the coast to 180 km offshore, coastal upwelling/downwelling anomalies and sea‐surface height anomalies along the coast of North America, resulting in coastal current anomalies and/or northward propagation of coastal waves, are important in determining Line‐P temperature anomalies.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".