Causes of increased dissolved inorganic carbon in the subsurface layers in the western shelfbreak and high latitudes basin in the Arctic Pacific sector
Bibliographic record
Abstract
Abstract The expansion of dissolved inorganic carbon (DIC)-rich water carried by the Pacific inflow creates a DIC maximum layer and exerts important influences on ocean acidification in the subsurface Arctic Ocean. This study analyzed shifts in the DIC distribution of the subsurface Arctic Ocean during 1998–2015 through hindcast simulation using a three-dimensional ocean-sea ice-biogeochemical model. For this purpose, the study was divided into two time periods (1998–2007 and 2008–2015). The results showed that the lower boundary layer of the Pacific Winter Water, defined as an isopycnal of 27 kg m −3 , became deeper by ∼50 m in the central Canada Basin and expanded northward during 2008–2015 relative to 1998–2007. Accordingly, the subsurface DIC maximum layer deepened and expanded northwards into the Makarov Basin at high latitudes around 85° N. During 2008–2015, DIC concentrations, averaged over a 50–250 m water column, increased significantly in the Chukchi-East Siberian Shelfbreak and Makarov Basin. The DIC increase over the shelfbreak is mainly attributable to increased local biological degradation and the transportation of DIC-rich water from the Chukchi Shelf through Barrow Canyon. Estimates of the DIC budget indicated that advection controlled the increase in DIC content in the Makarov Basin during 2008–2015. This is attributed to the shift of the ocean circulation pattern, in which the ocean current along the Chukchi-East Siberian Slope to the Makarov Basin became stronger during 2008–2015, promoting the transport of DIC-rich Pacific Water into the Makarov Basin.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".