Spatial analysis of large-scale patterns of forest tent caterpillar outbreaks
Bibliographic record
Abstract
A spatial analysis of forest tent caterpillar (Malacosoma disstria Hübner) outbreak data from Ontario indicates that previous studies examining the influence of forest heterogeneity and climate on outbreak vulnerability were pseudoreplicated. We adopted a spatially explicit modeling framework to re-examine, at several spatial scales, the influence of forest heterogeneity on outbreak duration, and also tested for effects of other plausible environmental factors including winter temperature, spring degree-day accumulation, and elevation. Of these, forest heterogeneity was the strongest predictor of the number years of defoliation recorded over three outbreak cycles. Nevertheless, correlations were inconsistent across districts and were often weak. We suggest that this is due either to the involvement of other factors or to neighbourhood effects associated with contagious population processes such as insect dispersal. The precise role of climatic perturbations in governing outbreak dynamics remains unclear but may be elucidated through studies at larger and smaller spatial scales.
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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 | 0.000 | 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 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".