Effects of climate change on the radial growth of shelterbelts across the brown, dark brown, and black soil zones of Saskatchewan
Bibliographic record
Abstract
Effects of climate change on the radial growth of shelterbelts across the brown, dark brown, and black soil zones of Saskatchewan Climate change poses many challenges for Saskatchewan agricultural producers. Landowners will face more frequent and intense weather events, increasing pest infestations and disease, and experience warmer and drier growing seasons under future climates. In response to this issue, several studies have named shelterbelts as a valuable strategy to buffer the negative effects of climate change, by helping protect producer's crops and livestock from the elements. However, the ability of shelterbelts to grow under a changed climate is unknown, and until it is determined, producers will be unable to benefit from the full potential of shelterbelts. We plan to predict the growth of four shelterbelts species across the brown, dark brown, and black soil zones of Saskatchewan to determine what species will be best suited to different areas within Saskatchewan under a changing climate. With this information, producers will be able to reap the benefits of shelterbelts, and better adapt 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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; 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".