Temperature variability in the Northeast Atlantic
Bibliographic record
Abstract
Time-series of sea temperature from the North Atlantic are statistically analysed and compared. We focus on the Norwegian coast and the Barents Sea, with supporting data from the waters off eastern Canada and the Faeroes. The longest time-series are sea surface temperature (SST) observations from Norwegian lighthouses, starting in the mid-1860s. Correlations all along the Norwegian coast are unlagged, suggesting that large-scale atmospheric forcing is important. Antisynchrony between Northeast and Northwest Atlantic sea temperature fluctuations is indicated. The North Atlantic Oscillation (NAO) is generally positively correlated to winter temperatures in Norwegian waters and negatively correlated to the temperature off Newfoundland. Correlations between the NAO and coastal SST on the west and south coasts of Norway are strong and persistent right back to the beginning of the observational record. However, Barents and Labrador Sea temperature seem to have been closely linked to the NAO only during the past 3-4 decades. Spectral analysis reveals that the four subsurface sea temperature series have oscillations from about 8 to about 14 years, the NAO has most variance at high frequencies ( < 1 year), while the SST series lie between. Article from Marine Science Symposia Vol. 219 - "Hydrobiological variability in the ICES Area, 1990-1999", symposium held in Edinburgh, 8-10 August 2001. To access the remaining articles please click on the keyword "MSS Vol. 219".
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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".