Marked contrast in wind-driven upwelling on the southeastern Nova Scotia coast in July of two years differing in ENSO conditions
Bibliographic record
Abstract
Abstract Upwelling occurs on several coasts of the world, but it has mostly been studied on eastern ocean boundaries. We investigated upwelling on a western ocean boundary for which limited information exists. Using daily in-situ data on sea surface temperature (SST), we found a marked contrast in coastal cooling between July 2014 (pronounced) and July 2015 (weak) at two locations 110 km apart on the Atlantic coast of Nova Scotia, Canada. These findings are consistent with a marked interannual difference in wind-driven upwelling. On the one hand, southwesterlies (which cause upwelling on this coast) were more frequent in July 2014 than in July 2015. On the other hand, Bakun’s upwelling index (which is based on wind data and geographic information) indicated that coastal upwelling was more common and intense in July 2014 than in July 2015, while the reverse was true for downwelling. Interestingly, a strong El Niño event occurred in July 2015, while no El Niño (or La Niña) conditions happened in July 2014. In a recent book evaluating upwelling systems around the world, the system that is the focus of the present study was not included. Therefore, our findings should stimulate future research on upwelling on the Atlantic Canadian coast, in that way helping to further develop the knowledge base for western ocean boundaries.
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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".