Mercury in the North Atlantic and Arctic Oceans - results of the 2014 GEOTRACES GEOVIDE & 2015 GEOTRACES \nTransArc II cruises.
Bibliographic record
Abstract
We will present the combined results of the French GEOTRACES GEOVIDE cruise in the North Atlantic Ocean and the 2015 German GEOTRACES cruise TransArc II in the central Arctic Ocean. Research vessel "Pourquoi pas?" sailed on May 15th from Lisbon to Greenland to arrive in Newfoundland on June 30th 2014, and icebreaker "Polarstern" sailed on August 17th from Tromsoe to explore the Nansen, the Amundsen and the Makarov basins, to arrive in Bremerhaven on October 15th 2015. Total mercury was sampled using ultra-trace clean rosettes and determined on board. In the Atlantic Ocean, surface waters of the Gulf Stream are cooled down as they travel north, and mix at the same time with waters exiting the Arctic Ocean via Fram Strait. These cool and dense surface waters dive to depth in the Greenland and Labrador seas. The North Atlantic Ocean predominantly receives Hg via atmospheric deposition from Europe and North America where industrial Hg emissions peaked in the 1970s. The Hg inputs to the Arctic Ocean are less well-constrained if not unknown. The current debate opposes a primary atmospheric with a river-dominated scenario. We find consistent surface depleted profiles in the North Atlantic Ocean, while we exclusively observe surface enrichments in the Arctic Ocean, at all sampling stations. We will make use of the combined data sets of both cruises to investigate how climate may impact Hg marine biogeochemical cycle, how anthropogenic Hg makes its way into the deep ocean and whether the temporal evolution of emissions is traceable in water masses of different ages. We will also put our new observations in context with recent numerical model evaluations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".