Genome sequences of six Phytophthora species threatening forest ecosystems
Bibliographic record
Abstract
The Phytophthora genus comprises of some of the most destructive plant pathogens and attack a wide range of hosts including economically valuable tree species, both angiosperm and gymnosperm. Many known species of Phytophthora are invasive and have been introduced through nursery and agricultural trade. As part of a larger project aimed at utilizing genomic data for forest disease diagnostics, pathogen detection and monitoring (The TAIGA project: Tree Aggressors Identification using Genomic Approaches; http://taigaforesthealth.com /), we sequenced the genomes of six important Phytophthora species that are important invasive pathogens of trees and a serious threat to the international trade of forest products. This genomic data was used to develop highly sensitive and specific detection assays and for genome comparisons and to make evolutionary inferences and will be useful to the broader plant and tree health community. These WGS data have been deposited in the International Nucleotide Sequence Database Collaboration (DDBJ/ENA/GenBank) under the accession numbers AUPN01000000, AUVH01000000, AUWJ02000000, AUUF02000000, AWVV02000000 and AWVW02000000.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".