Sea ice convergence along the Arctic coasts of Greenland and the Canadian Arctic Archipelago: Variability and extremes (1992–2014)
Bibliographic record
Abstract
Abstract After the summer of 2013, a convergence‐induced tail in the thickness distribution of the ice cover is found along the Arctic coasts of Greenland and Canadian Arctic Archipelago. Prompted by this, a normalized ice convergence index (ICI) is introduced to examine the variability and extremes in convergence in a 23 year record (1992–2014) of monthly ice drift. Large‐scale composites of circulation patterns, characteristic of regional convergence and divergence, are examined. Indeed, the ICI shows the June 2013 convergence event to be an extreme (i.e., ICI > 2). Furthermore, there is a cluster of 9 months over a 17 month period with positive ICIs (i.e., >1) following the record summer minimum ice extent (SMIE) in 2012; the imprint of ice dynamics from this cluster of positive ICIs likely contributed to higher SMIEs in 2013 and 2014. The impact of convergence on SMIE is discussed, and the increase in Arctic ice volume in 2013 is underscored.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".