Bibliographic record
Abstract
Windstorms are common events in midlatitude west coast climates yet little is known about their long-term history and influence on regional forests. In this paper, we present a procedure that detects the timing and frequency of these high-wind events (HWEs) along the Pacific Northwest coast of North America using crossdated tree-ring measurements and detrended tree-ring chronologies derived from windsnapped trees. Our results show that abrupt changes in ring width patterns closely match dates of known HWEs and can serve as a nonclimatic basis for crossdating. Experimentation with different growth suppression and release criteria revealed that either a 50% decrease or a 50% increase in radial growth relative to the mean index value provided the best criterion for detecting windstorm-related growth anomalies. Comparing these results with the known occurrence of windstorms during the past century successfully identified all known major wind events during the study period. Low correlations between tree growth and climatic variables further imply that HWEs are the principal cause of interannual growth variations. Accordingly, we discuss the application of our procedure toward the development of a multicentury reconstruction of HWEs, a long-term analysis of decadal climate variability and HWEs, and the ecological role of HWEs in Pacific Northwest and other west coast forests.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".