Quantifying the Impact of River Discharge on Nearshore Sea Ice in the Alaskan Arctic
Bibliographic record
Abstract
The Arctic is increasingly vulnerable to global warming, leading to shortening winter seasons, later freezes, and earlier breakups of sea ice. This project quantifies changes in sea ice seasonality from 1979 - 2023 using passive microwave data and sea ice climate indicator variables. Our results are consistent with those previously published by Bliss et al. (2019) finding statistically significant positive trends in the ice-free season length. We find the most rapid changes in the Chukchi Sea off the northwestern coast of Alaska. Based on current trends, we find that this region could become ice-free in the next 80 years. We also quantify the impact of river discharge on nearshore sea ice, finding correlation between the peak discharge and 90% sea ice concentration threshold dates for the region adjacent to the Mackenzie River delta. The same relationship does not exist near the Yukon River delta, with sea ice melting approximately 60 days before river discharge peaks. These findings will support future work analyzing the impact of ice on Arctic coastal biogeochemistry.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".