New Constraints on the Physical and Biological Controls on the Silicon Isotopic Composition of the Arctic Ocean
Bibliographic record
Abstract
The silicon isotope composition of silicic acid, δ30Si(OH)4, in the deep Arctic Ocean is anomalously heavy compared to all other deep ocean basins. To further evaluate the mechanisms leading to this condition, δ30Si(OH)4 was examined on US GEOTRACES section GN01 from the Bering Strait to the North Pole. Isotope values in the polar mixed layer showed a strong influence of the transpolar drift. Drift waters contained relatively high [Si(OH)4] with heavy δ30Si(OH)4 consistent with the high silicate of riverine source waters and strong biological Si(OH)4 consumption on the Eurasian shelves. The maximum in silicic acid concentration, [Si(OH)4], within the double halocline of the Canada Basin formed a local minimum in δ30Si(OH)4 that extended across the Canada Basin, reflecting the high-[Si(OH)4] Pacific source waters and benthic inputs of Si(OH)4 in the Chukchi Sea. δ30Si(OH)4 became lighter with the increase in [Si(OH)4] in intermediate and deep waters; however, both Canada Basin deep water and Eurasian Basin deep water were heavier than deep waters from other ocean basins. A preliminary isotope budget incorporating all available Arctic δ30Si(OH)4 data confirms the importance of isotopically heavy inflows in creating the anomalous deep Arctic Si isotope signature, but also reveals a surprising similarity in the isotopic composition of the major inflows compared to outflows across the main gateways connecting the Arctic with the Pacific and the Atlantic. This similarity implies a major role of biological productivity and opal burial in removing light isotopes entering the Arctic Ocean from rivers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".