An Epidemiological Comparison of the US and Canadian <i>Plum pox virus</i> Eradication Programs
Bibliographic record
Abstract
Plum pox virus (PPV) was first detected in North America in 1999 in Pennsylvania, and the following year in Ontario, Canada. In response to these outbreaks, both countries implemented eradications programs in an effort to eradicate the virus before it could have a significant effect on the Prunus industry in their respective countries. The objectives of this study were to: (i) quantify the impact of the US and Canadian PPV eradication programs on the spatial and temporal dynamics of PPV in Pennsylvania and Ontario; and (ii) compare the detection efficiencies of the US and Canadian PPV sampling systems. Ripley's K function revealed PPV-positive Prunus blocks in Pennsylvania to be clustered between distances of 0.7 and 4.3 km in 2000, while in Ontario, PPV-positive blocks were clustered between distances of 1 and 25 km over the period 2006-2009. A simulation model was developed to determine the relative detection efficiencies of the US and Canadian PPV eradication programs. The US eradication program was found to have a detection efficiency of 71.7%, whereas the Canadian eradication program had a detection efficiency of 40.5%. The data generated in this study should help to improve the PPV eradication programs currently used in the US and Canada, as well as provide a scientific basis to evaluate future eradication programs. Accepted for publication 23 May 2012. Published 23 July 2012.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".