Evaluation of Sampling and Testing Efficiencies of <i>Plum pox virus</i> Eradication Programs in Pennsylvania and Ontario
Bibliographic record
Abstract
Plum pox virus (PPV) was first detected in the United States in Pennsylvania in 1999 and in Ontario, Canada in 2000. Following a 10-year survey and eradication program, PPV was officially declared eradicated in Pennsylvania in 2009. Although incidence of PPV was greatly reduced from 2000 to 2008, PPV remains present in Ontario. The objective of this study was to compare how the Pennsylvania and Ontario PPV eradication programs affected the probability of detecting PPV at the leaf, scaffold, tree, and Prunus orchard block scales. A simulation model was developed to evaluate the sampling and testing efficiency of the two programs. At the tree scale, the Pennsylvania sampling and detection protocols had a detection efficiency of 71.8% compared with 40.5% for the Ontario program. Several components in the Pennsylvania and Ontario PPV eradication programs affected PPV detection efficiency. A stratified (by tree scaffold) random sampling design did not improve PPV detection efficiency in either program, compared with a simple random sampling design to select leaves for enzyme-linked immunosorbent assay (ELISA) testing. Detection efficiency for both programs increased with sample size but gains in detection efficiency diminished as sample size increased. There was good agreement (between the commercial ELISA kit used in Pennsylvania and the kit used in Ontario) at the leaf and scaffold scales but not the tree scale. Based on simulation modeling, the Pennsylvania PPV eradication program required that >2 PPV-positive trees must be present within a Prunus block to achieve a 95% probability of correctly detecting PPV at the block scale, whereas the Ontario program required >5 PPV-positive trees within a block to achieve 95% probability of detection. The results from this study have important implications with regard to the efficiency of the two eradication programs to detect PPV-positive trees.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".