Dynamics of the impacts of <i>Pratylenchus penetrans</i> on Gisela® cherry rootstocks
Bibliographic record
Abstract
Abstract Sweet cherry growers are increasingly using semi-dwarfing rootstocks, including the Gisela® series, when replanting orchards. Little is known of the susceptibility of these new cherry rootstocks to Pratylenchus penetrans , a recognized pest of temperate fruit trees worldwide. Two field experiments were planted in 2010, one in the Okanagan Valley of British Columbia and one in the Annapolis Valley of Nova Scotia. Each experiment was a factorial combination of three rootstocks (Gi.3, Gi.5, and Gi.6) × three training systems, with six replicate four-tree plots of each of the nine combinations. Both sites were fumigated prior to planting and population densities of P. penetrans in roots and root-zone soil were subsequently monitored from 2013 through 2017. None of the P. penetrans population parameters (nematodes/kg soil, nematodes/g fine root, and nematodes/kg soil including roots) differed among rootstocks at either site, suggesting that the rootstocks did not differ in their ability to host P. penetrans . At the British Columbia site only there was an inverse relationship between P. penetrans population densities and tree size for Gi.3 trees in four years and for Gi.6 in 2017, suggesting that Gi.3 rootstock is less tolerant than Gi.5 and Gi.6 rootstocks.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".