Calibration of an ice-core glaciochemical (sea-salt) record with Sea-ice variability in the Canadian Arctic
Bibliographic record
Abstract
Abstract Correlation between glaciochemical time Series from an ice core collected on Devon Ice Cap, Nunavut, Canada, and gridded time Series of Sea-ice concentrations reveals Statistically Significant inverse relationships between Sea-salt concentrations (mainly Na+, Mg2+and Cl–) in the ice core and Sea-ice cover in Baffin Bay over the period 1980–97. An empirical orthogonal function (Eof) analysis performed on all major ions Shows that the dominant mode of glaciochemical variability (Eof1) represents a Sea-salt Signal, which correlates best with Sea-ice concentration in Baffin Bay. On a Seasonal basis, the Strongest and most Spatially extensive anticorrelations are found in Baffin Bay during the fall, followed by Spring, Summer and winter. These results Support the notion that increased open-water conditions in Baffin Bay during the Stormy Seasons (fall and Spring) promote increased production, transport and deposition of Sea-salt aerosols on Devon Ice Cap. Comparison of ice-core time Series of Eof1, δ18O and melt percentage, with air temperatures recorded in Upernavik, Greenland, Suggests that ice-cover variations in Baffin Bay over the past ∽145 years were dynamically rather than thermodynamically controlled, with periods of Strengthened cyclonic circulation leading to increased open-water conditions, and a greater Sea-salt flux on Devon Ice Cap.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".