Collaborative Research: Arctic Sensitivity to Climate Perturbations and a Millennial Perspective on Current Warming Derived from Shrinking Ice Caps
Bibliographic record
Abstract
The goal of this proposal is to provide a millennial context for current warming and to better constrain the nature of abrupt climate changes over the past 5000 years in the North Atlantic sector of the Arctic. This goal will be addressed with the powerful datasets derived from radiocarbon-dated vegetation preserved beneath ice caps for centuries to millennia, but now being exposed annually by current ice-margin retreat across northeastern Canada and West Greenland. These chronologies define the pattern and timing of abrupt summer coolings in the recent past and place current warming in a millennial context. 14C dating of vegetation will be complemented by measuring in situ 14C inventories in recently exposed rock surfaces, providing essential temporal constraints on the duration of ice-covered and ice-free conditions throughout the Holocene. Combined, these two datasets will provide the most secure evidence for the character of current summer warming by explicitly dating when the region was last as warm as present. Comparing our climate reconstructions with on-going studies in NW Europe will help to separate the roles of unforced variability from hemispherically symmetric forcing as causes for abrupt climate change. Research activities under this award will be made accessible to indigenous peoples by translating the goals and eventual results into Inuktitut, through posters that describe the research, and by offering public lectures in Iqaluit, the capital of Nunavut, and at Qikiqtarjuaq, where INSTAAR has long had a presence. This research program will train a PhD and MSc student, and provides opportunities for undergraduate students to become involved with research, building on successful traditions from previous years.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".