A Five-Year Record of Summer Melt on Eurasian Arctic Ice Caps
Bibliographic record
Abstract
Abstract Climatologies and annual anomaly patterns (2000–04) of melt season duration and dates of melt onset/freeze-up on Eurasian Arctic ice masses were derived from Quick Scatterometer (QuikSCAT) backscatter data. Severnaya Zemlya, Russia, has later melt onset, earlier freeze-up, and shorter melt seasons than Svalbard, Norway/Novaya Zemlya, Russia. In all three archipelagos 2001 was the longest melt season and 2000 was the shortest. Anomalously long (short) melt seasons on Svalbard were associated with negative (positive) sea ice concentration anomalies along the north coast in June and August. Annual mean melt duration was strongly correlated with the mean (June + August) NCEP–NCAR reanalysis 850-hPa air temperature, allowing reconstruction of melt durations for the period of 1948–2005. The 2000–04 pentad had the second or third longest mean melt duration of all pentads in the 1950–2004 epoch, while the 1950–54 pentad probably had the longest. Integration of these results with previous results from Greenland and the Canadian Arctic identifies 2002 as the longest melt season in the 2000–04 period across the Arctic as a whole, and 2001 as the shortest. Correlation of melt duration anomalies for 19 discrete regions identifies seven spatially coherent areas of the Arctic with common patterns of variability in annual melt duration.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".