A tracer study of the Arctic Ocean's liquid freshwater export variability
Bibliographic record
Abstract
We present an analysis of the variability of the liquid Arctic freshwater (FW) export, using a simulation from the Community Climate System Model Version 3 (CCSM3) that includes passive tracers for FW from different sources. It is shown that the FW exported through the western Canadian Arctic Archipelago (CAA) comes mainly from the Pacific and from North American runoff. The variability of the FW export from both of these sources is generally in phase, due to the strong influence of variations of the velocity anomaly on the CAA FW export variability. The velocity anomaly in the CAA is in turn mainly governed by variations in the large‐scale atmospheric circulation (i.e., the Arctic Oscillation). In Fram Strait, the FW export is mainly composed of Eurasian runoff and FW of Pacific origin. The variability of the Fram Strait FW export is governed both by changes in the velocity and in the FW concentration, and the variability of the FW concentration from the two largest sources is not in phase. The Eurasian runoff export through Fram Strait depends strongly on the release of FW from the Eurasian shelf, which occurs during years with an anticyclonic circulation anomaly (negative Vorticity index) and takes 3 years to reach Fram Strait after leaving the shelf. In contrast, the variability of the Pacific FW export through Fram Strait is mainly controlled by changes in the Pacific FW storage in the Beaufort Gyre, with an increased export during years with a cyclonic circulation anomaly (positive Vorticity index).
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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 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".