Modeling Dissolved and Particulate Th in the Canada Basin: Implications for Recent Changes in Particle Flux and Intermediate Circulation
Bibliographic record
Abstract
Abstract Global climate change has had large impacts on the Arctic region including rapid reductions in sea ice and rapid increases in surface air temperatures. Documenting the consequences of these changes in the Arctic Ocean is difficult, however, because accessibility limits observations in space and time and aliases measurements. This problem can be alleviated by using geochemical tracers, which can act as natural integrators, allowing us to determine net changes over regions and years. One such tracer is Th. We use measurements and an off‐line scavenging model forced by ANHA4, a regional configuration of the NEMO general circulation model, to investigate changes in the Canada Basin in the years 2002–2015. Observations show a clear decrease in Th in intermediate layers, particularly in the internal Canada Basin. The model reproduces the observed changes in Th concentration profiles. Using the model to determine the origin of the reduction shows that the decrease is due to both higher particle fluxes from increased productivity resulting from the reduction in sea ice cover and increased circulation and stirring by mesoscale eddies increasing lateral exchange between the productive coastal regions and less productive internal Canada Basin. The circulation model clearly shows increased velocities as the ice cover has decreased and storms have increased.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".