Estimates of emerald ash borer (Coleoptera: Buprestidae) larval galleries in branch samples from asymptomatic urban ash trees (Oleaceae)
Bibliographic record
Abstract
Abstract Agrilus planipennis(Coleoptera: Buprestidae), is causing extensive mortality of ash (FraxinusLinnaeus; Oleaceae) in North America. Once detected in an area, resource managers require methods to obtain estimates that could improve management decisions. We studied the within-crown and within-branch distribution and abundance ofA. planipennisfeeding galleries by sampling 3-m-long branches from asymptomatic urban ash trees and subdividing each branch into 12 sections of 25 cm each. We found galleries in all 12 sections of some, but not all, branches. Section was a significant source of variation inA. planipennisgallery density/m2of branch surface area. A comparison of predictive power and efficiency of estimates for samples of increasing length, and for samples of the same length but consisting of different combinations of sections, revealed that those based on the two basal 25-cm sections of a branch from the lower-crown or mid-crown of an asymptomatic tree were less accurate and precise than those based on more sections, but were the most cost effective. Whittling more sections per branch, irrespective of the combinations of branch sections per length, improved predictive power but reduced cost effectiveness. We also observed that crown level was not important, and aspect was only marginally so, when estimating gallery abundance per sampled branch.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".