Climate Change Impacts to the Arctic Ocean Revealed From High Resolution GEOTRACES <sup>210</sup>Po‐<sup>210</sup>Pb‐<sup>226</sup>Ra Disequilibria Studies
Bibliographic record
Abstract
Abstract Climate change is transforming the Arctic Ocean in unprecedented ways which can be most directly observed in the systematic decline in seasonal ice coverage. From the collection and analysis of particulate and dissolved activities of 210Po and 210Pb from four deepwater superstations, as a part of the US Arctic GEOTRACES cruise during 2015, and in conjunction with previously published data, the temporal and spatial variations in their activities, inventories and residence times are evaluated. The results show that the partitioning of particulate and dissolved phases has changed significantly in the 8 years between 2007 and 2015, while the total 210Po and 210Pb activities have remained relatively unchanged. Observed total 210Po/210Pb activity ratio was less than unity in all deepwater stations, implying disequilibria in the entire water column. From the distribution of total 210Po and 210Pb in the upper 500 m of all major Arctic Basins, the derived scavenging efficiencies decrease as per the following sequence: Makarov Basin > Gakkel Bridge > Canada Basin Nansen Basin ∼ Amundsen Basin > Alpha Ridge, which is the reverse order of the calculated residence times of 210PoT. The scavenging intensities differ between the fully ice‐covered, partially ice‐covered, and no ice‐covered stations, as observed from the differences in the average activities of 210Po and 210Pb. The average settling velocity of particulate matter based on the 210Pb activity is similar to the published values based on 230Th, indicating removal mechanism(s) of Th and Pb is (are) similar.
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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 | 0.000 |
| 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) | 0.000 | 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".