SPATIAL AND TEMPORAL PATTERNS OF CARBON DIOXIDE EXCHANGE FOR A WET SEDGE PLANT COMMUNITY, MELVILLE ISLAND, NU (2015)
Bibliographic record
Abstract
In 2015, Automated Soil CO2 Exchange (ACE) Stations were deployed at the Cape Bounty Arctic Watershed Observatory (CBAWO) to quantify the contribution of CO2 exchange from wet sedge vegetation. The wet sedge vegetation type is of specific interest as it is the most productive community type in the High Arctic. These communities are commonly regarded in past studies as carbon sinks during their entire growing season, although the scale and key controls are not completely understood. In addition, warming of the High Arctic enhances wet sedge growth, which may result in an increase of the percentage of land occupied by wet sedge meadows. This in turn has the capability of significantly altering the carbon balance of high Arctic landscapes. The objective of these data files is to determine the CO2 exchange rate in these settings, utilizing the ACE systems. The measurements from each chamber were automatically recorded every 30 minutes from July 3 2015 to August 7 2015. Active layer depth, photosynthetically active radiation (PAR), soil temperature and soil moisture measurements were also collected in conjunction with the net CO2 exchange rate (NCER). The r esults indicate that wet sedge vegetation in this area does represent a carbon sink through photosynthetic processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".