Spatial variability in carbon dioxide exchange processes within wet sedge meadows in the Canadian High Arctic
Bibliographic record
Abstract
Wet sedge meadows are the most productive plant communities in the High Arctic. However, the controls on carbon dioxide (CO2) exchange processes within wet sedge communities – and the scale at which they operate – are poorly understood. Here, the factors controlling CO2 exchange of wet sedge meadows experiencing different moisture regimes are examined. Environmental data are used to create predictive models of CO2 exchange on multiple temporal scales. Automated chamber systems recorded CO2 fluxes at 30-minute intervals at wet sedge sites in the Canadian High Arctic from June to August in 2014 and 2015. Static chambers were also deployed over a larger spatial extent in 2014. Our results show that wet sedge communities were strong CO2 sinks during the growing season (−7.67 to −44.36 g C•m−2). CO2 exchange rates in wetter and drier areas within wet sedge meadows differed significantly (Wilcoxon, p Citation: Wright C M, Blaser A C, Treitz P M, et al. Spatial variability in carbon dioxide exchange processes within wet sedge meadows in the Canadian High Arctic. Adv Polar Sci, 2021, 32(1): 1-19, doi: 10.13679/j.advps.2020.0033
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".