Correlation of river water and local sea‐ice melting on the Laptev Sea shelf (Siberian Arctic)
Bibliographic record
Abstract
Hydrographic and stable isotope (δ 18 O) data from four summer surveys in the Laptev Sea are used to derive fractions of sea‐ice meltwater and river water. Sea‐ice meltwater fractions are found to be correlated to river water fractions. While initial heat of river discharge is too small to melt the observed 0–158 km 3 of sea‐ice meltwater, arctic rivers contain suspended particles and colored dissolved organic material that preferentially absorb solar radiation. Accordingly, heat content in surface waters is correlated to river water fractions. But in years when river water is largely absent within the surface layer, absolute heat content values increase to considerably higher values with extended exposure time to solar radiation and sensible heat. Nevertheless, no net sea‐ice melting is observed on the shelf in years when river water is largely absent within the surface layer. The total freshwater volume of the central‐eastern Laptev Sea (72–76°N, 122–140°E) varies between ~1000 and 1500 km 3 (34.92 reference salinity). It is dominated by varying river water volumes (~1300–1800 km 3 ) reduced by an about constant freshwater deficit (~350–400 km 3 ) related to sea‐ice formation. Net sea‐ice melt (~109–158 km 3 ) is only present in years with high river water budgets. Intermediate to bottom layer (>25 salinities) contain ~60% and 30% of the river budget in years with low and high river budgets, respectively. The average mean residence time of shelf waters was ~2–3 years during 2007–2009.
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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 | 0.000 | 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) | 0.001 | 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 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".