How the State of the Arctic Impacts Upon Global Efforts to Limit Climate Change
Bibliographic record
Abstract
Relatively few people have visited the Earth’s icy cap, the Arctic. Cold and inhospitable, and dark for several months of the year, the region has been home to Inuit, Saami and other indigenous peoples for thousands of years. Adapting to the harsh conditions required plenty of ingenuity and persistence. Yet, the Arctic region is changing, and changing rapidly. The sea ice covering most of the Arctic Ocean, the vast Greenland ice sheet, the snow cover on land and the large area of frozen ground called permafrost, are all melting away. Why? Scientists are unanimous in the verdict: climate change caused by man-made emissions of greenhouse gases (Pachauri et al., 2014). The Arctic has been warming twice faster that the global average as a result (Overland et al., 2015), causing the extensive melting documented by several decades of satellite records and measurements on the ground (Stroeve et al., 2012; Mouginot et al., 2019; Chadburn et al., 2017). It is no wonder that the Arctic is sometimes called the barometer of global risk from climate change
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".