Multi decadal glacier area fluctuations in Pan-Arctic
Bibliographic record
Abstract
Abstract. The shrinking of land-terminating glaciers and ice caps (GIC) has been documented in high-latitude regions, even though repeat observations upon which to base such studies have been limited in space. Here, we present a new record of satellite-derived area changes for 321 land-terminating GIC throughout Pan-Arctic and for the W. Canada and W. US, with focus on the period from mid-1980s to late-2000s/2011 (the last ca. 25 yr). The mean shrinking rate was −0.06±0.01 km2 yr−1 during a period with climate warming. Most of the observed GIC shrank in area, more so than previously believed: while only 8% advanced. The analysis indicates that the observed GIC have lost an arithmetic average of one-fifth of their area since the mid-1980s (equal to a shrinking rate of ca. −1% yr−1), with the highest rate of loss of −40±4% (−1.7 % yr−1) in Alaska, and the lowest rate of loss of −12±3% (−0.5 % yr−1) in Arctic Russia.
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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 | 0.000 | 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".