A Sequential Sampling Plan for Counts of <I>Adelges tsugae</I> on Individual Eastern Hemlock Trees
Bibliographic record
Abstract
A sequential sampling plan was developed to estimate density of sistens of the invasive exotic hemlock woolly adelgid, Adelges tsugae (Annand), by counting adelgids on new shoots of four branch tips sampled from the lower half of the live crown of individual, asymptomatic eastern hemlock trees. The y-intercepts and slopes for the relationship between observed mean and variance of A. tsugae counts were similar for North Carolina and for 2 years of data collected from Virginia; thus, data were pooled to create one regression equation that was used to develop a count-based sequential sampling plan. Validation data sets were obtained in West Virginia and by randomly selecting half of the trees sampled in North Carolina and Virginia, trees not used previously to develop the sampling plan. Validation of the combined North Carolina–Virginia sampling plan showed that the model performed as specified. This plan should allow for estimation of adelgid population changes on a tree over time, provided the tree has not declined due to A. tsugae infestation. This plan can also be used to assess chemical or biological treatment effects on A. tsugae, provided such treatments do not fundamentally alter the mean–variance relationship.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".