Peatlands and Global Carbon Cycle Modeling: Peatland Ecosystem Analysis and Training Network (PeatNet) Workshop; Durham, New Hampshire, 14–15 May 2009
Bibliographic record
Abstract
Peatlands cover 3–5% of the global land surface, contain about 20% of all terrestrial organic carbon, and contribute significantly to total biogenic methane emissions to the atmosphere. More than one third of northern peatlands contain permafrost. Northern peatlands are likely to experience the consequences of climate warming earlier, more rapidly, and to a greater degree than many of the Earth's other major ecosystems. To map out how peatlands could be incorporated into global‐scale coupled climate‐carbon models and to determine what research and model development would be needed to overcome major obstacles, 17 scientists with expertise in peatland ecology, biogeochemistry and vegetation modeling, and global‐scale coupled climate‐carbon modeling participated in a workshop organized by the U.S. National Science Foundationsponsored PeatNet (http://www.peatnet.siu.edu/).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".