Predicting effects of climate change on Swiss needle cast disease severity in Pacific Northwest forests
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Swiss needle cast of Douglas-fir (Pseudotsuga menziesii) is caused by the ascomycete Phaeocryptopus gaeumannii. Symptoms are foliage chlorosis and premature needle abscission due to occlusion of stomata by the ascocarps of the pathogen, resulting in impaired needle gas exchange. Growth losses of 20%-50% due to Swiss needle cast have been reported for approximately 150 000 ha of Douglas-fir plantations in western Oregon since 1996. In the western Coast Range of Oregon and in New Zealand, winter temperature is strongly correlated with pathogen abundance. Models for predicting disease severity based on winter temperature account for 77% and 78% of the variation in 1- and 2-year-old needles, respectively, for western Oregon sites and approximately 80% for New Zealand. A trend of temperatures increasing by 0.2–0.4 °C during the winter months and spring precipitation increasing by 0.7–1.5 cm/decade since 1970 suggests that regional climate trends are influencing the current distribution and severity of Swiss needle cast disease. Continuing winter temperature increases predicted for the Pacific Northwest of approximately 0.4 °C/decade through 2050 suggest that the severity and distribution of Swiss needle cast is likely to increase in the coming decades as a result of climate change, with significant consequences for Pacific Northwest forests.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it