Assessment and improvement of the sea ice processing for dissolved inorganic carbon analysis
Bibliographic record
Abstract
Abstract Dissolved inorganic carbon (DIC) is an important parameter to characterize the biogeochemical processes in sea ice and across the ocean‐sea ice‐atmosphere interface. The main challenge in bulk sea ice processing for DIC analysis is to melt the ice core without exposure to the air, which otherwise might contaminate the sample. A common practice is to seal the ice core in a gas‐tight plastic bag and remove the air gently using a syringe or a hand pump. However, this procedure is time‐consuming and the uncertainty in DIC concentration processed in this way has not been fully accessed. In this study, we modified the method by using a vacuum sealer and evaluated this procedure by examining the impact of ice sample processing, biological activity, gaseous CO 2 initially present in sea ice, and the presence of ikaite (CaCO 3 ·6H 2 O) crystals. The results show that no loss or gain in DIC occurs during the evacuation and ice melting process and that it might not be necessary to pre‐poison the ice samples during the ice melting process. In addition, gaseous CO 2 initially present in sea ice has a negligible impact on DIC analysis. If detectable ikaite crystals are present in sea ice, the measurement results should be referred to total inorganic carbon instead of DIC. The field test at Station Nord in Greenland demonstrates that the modified method is simple and quick to use even under the most remote and extreme environments.
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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 | 0.001 | 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 | 0.001 | 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 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".