Quantification of ikaite in first and multi year sea ice
Bibliographic record
Abstract
Ikaite (CaCO₃•6H₂O) is a metastable calcium carbonate mineral that forms in all types of sea ice that may play a significant role in the sea ice driven carbon pump, particularly with the increasing abundance of seasonal sea ice in the Arctic. Due to difficulties in determining its concentration and abundance, the spatial and temporal dynamics, and therefore the significance, of ikaite are poorly understood. To improve knowledge of ikaite in sea ice, a new method of quantification using dissolved inorganic carbon (DIC) analysis was developed and tested at the Sea-ice Environmental Research Facility (SERF), at Station Nord, Greenland, and at Cambridge Bay, Nunavut. Environmental parameters, including temperature, salinity, total alkalinity (TA), and DIC were also measured at all sampling sites. Ikaite concentrations ranged from 8 to 2595 μmol kg⁻¹ and were generally highest in low temperature, high salinity sea ice with high TA:DIC ratios. Results indicate that the new method of ikaite quantification is an effective technique that can be used in the future to improve understanding of ikaite and its role in carbon dynamics in ice covered seas.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".