Spatial prediction of the onset of spruce budworm defoliation
Bibliographic record
Abstract
A logistic regression model for spatially explicit predictions of the likelihood of an onset of stand-level spruce budworm (Choristoneura fumiferana, Clemens) defoliation in a 15 000 km 2 study area in northern British Columbia, Canada is developed. Predictions are derived from stand (volume and needle biomass) and topographic attributes (distance from nearest river, distance from previous year defoliation, and stand elevation) collected during the first 12 years of a current budworm outbreak. The likelihood of an onset of defoliation increased with an increase in stand volume and biomass of current needles and it decreased with an increase in the distance to the nearest river and to the nearest stand with a defoliation recorded for the year prior to the year of prediction. Stands located at higher elevations sustained less defoliation than stands located at lower elevations. A single model is assumed adequate for predictions throughout an entire outbreak cycle. Observed and predicted relative frequencies of locations with an onset of defoliation compared relatively well. Key words: Choristoneura fumiferana; Picea; logistic regression; nearest neighbour distance
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".