Author Correction: North Atlantic variability and its links to European climate over the last 3000 years
Bibliographic record
Abstract
In the original version of this Article, the third sentence of the first paragraph of the “Changes in the input of polar waters into the Labrador Sea” section of the Results originally incorrectly read ‘During the spring-summer months, after the winter convection has ceased in the Labrador Sea, its northwest boundary currents (the EGC and IC) support restratification of the surface ocean through lateral transport.’ The correct version states ‘northeast’ instead of ‘northwest’. The fifth sentence of the second paragraph of the same section originally incorrectly read “In contrast, in the western section of the Nordic Seas, under the presence of warm Atlantic waters of the Norwegian Current, Nps was found to calcify deeper in the water column (100–200 m), whereas in the east under the influence of the EGC polar waters it calcified closer to the surface at a similar depth as Tq23.” The correct version states ‘eastern’ instead of ‘western’ and ‘west’ instead of ‘east’.The seventh sentence of the same paragraph originally incorrectly read “Small/large differences in Δδ18ONps-Tq indicating increased/decreased presence of warm and salty Atlantic IC waters vs. polar EGC waters in the upper water column, respectively.” The correct version starts ‘Large/small’ rather than ‘Small/large’.These errors have been corrected in both the PDF and HTML versions of the Article.
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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 | 0.003 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.064 | 0.034 |
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".