Bibliographic record
Abstract
Abstract. Global warming has already substantially altered the Arctic cryosphere. Due to the Arctic warming amplification, the temperature is increasing more strongly leading to pervasive changes in this area. Recent years were notably marked by melt records over the Greenland Ice Sheet while other regions such as Svalbard seem to remain less influenced. This raises the question of the current state of the Greenland Ice Sheet and the various ice caps in the Arctic for which few studies are available. We here run the Regional Climate Model (RCM) Modèle Atmosphérique Régional (MAR) at a resolution of 6 km over 4 different domains covering all the Arctic grounded cryosphere to produce a unified Surface Mass Balance product from 1950 to present day. We also compare our results to large-scale indices to better understand the heterogeneity of the evolutions across the Arctic and their links to recent climate change. We find a sharp decrease of SMB over the western Arctic (Canada and Greenland), in relationship with the atmospheric blocking situations that have become more frequent in summer, resulting in a 41 % increase of the melt rate since 1950. This increase is not seen over the Russian Arctic and Svalbard permanent ice areas, where melt rates have increased by only 9 % on average, illustrating a heterogeneity in the Arctic SMB response to global warming.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.025 | 0.024 |
| Insufficient payload (model declined to judge) | 0.113 | 0.104 |
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".