Climate change experiments in temperate grasslands: synthesis and future directions
Bibliographic record
Abstract
The immediate need to understand the complex responses of grasslands to climate change, to ensure food supplies and to mitigate future climate change through carbon sequestration, necessitate a global, synthesized approach. Numerous manipulative experiments have altered temperature or precipitation, often in conjunction with other interacting factors such as grazing, to understand potential effects of climate change on the ecological integrity of temperate grasslands and understand the mechanisms of change. Although the different ways in which temperature and precipitation may change to effect grasslands were well represented, variability in methodology limited generalizations. Results from these experiments were also largely mixed and complex; thus, a broad understanding of temperate grassland responses to these factors remains elusive. A collaboration based on a set of globally dispersed, inexpensive experiments with consistent methodology would provide the data needed to better understand responses of temperate grassland to climate change.
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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 | 0.026 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".