Terrestrial geosystems, ecosystems, and human systems in the fast-changing Arctic: research themes and connections to the Arctic Ocean
Bibliographic record
Abstract
In parallel to rapid sea-ice loss and other climate impacts in the Arctic Ocean, large-scale changes are now apparent in northern landscapes and associated ecosystems. Arctic communities are increasingly vulnerable to these changes, including effects on food security, water quality, and land-based transport. The project “Terrestrial Multidisciplinary distributed Observatories for the Study of Arctic Connections” (T-MOSAiC) was conducted under the auspices of the International Arctic Science Committee over the period 2017–2022. The aim was to generate multiauthored syntheses, protocols, and observations toward an improved understanding of Arctic terrestrial change, and to identify priorities for northern research, monitoring, and policy development. This special collection of Arctic Science covers a broad range of these themes, including limnological insights into northern lakes and rivers, a set of protocols for permafrost and vegetation monitoring, an integrated perspective on Arctic roads and railways to bridge the social and natural sciences, snow and ice studies at the coastal margin of the Last Ice Area, and Indigenous perspectives on Arctic and global conservation. The contributions summarized in this introductory article to the T-MOSAiC special collection include recommendations for the future, and they illustrate the immense value of Arctic collaborations that bring together researchers across disciplines, nations, and cultures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".