Five years of winter climate change-related research in the Canadian low Arctic: What have we learned?
Bibliographic record
Abstract
Abstract The importance of the fall, winter and spring periods to ecosystem functioning and biogeochemical cycling in tundra has only become apparent in the past two decades. Our research group has been conducting winter climate change-related studies at a low arctic tundra site near Daring Lake, north of Yellowknife in northern Canada for the past five years. Most of these studies have focused on the biogeochemical interactions between plants, soils, and soil microbes during fall, winter and spring, and on their responses to experimentally deepened snow. In addition, we have measured trace gas production and isotopic nitrogen tracer distributions among plant and soil components in several vegetation-types. The central goal has been to understand the potential importance of cold season soil N transformation processes to ecosystem-level biogeochemistry during the subsequent plant growing season, and then to develop predictions of how changes in winter climate may impact these seasonal processes. In this talk, I will present a synthesis of those studies, emphasizing temperature-moisture interactions, and highlighting future research priorities.
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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 | 0.003 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".