Uncovering the hologenomic basis of an extraordinary plant invasion
Bibliographic record
Abstract
Abstract While invasive species are a key driver of the global biodiversity crisis, the drivers of invasiveness remain debated. To investigate the genomic basis of invasiveness in plants, we use the invasive weed Ambrosia artemisiifolia , introduced to Europe in the late 19 th century, resequencing 655 ragweed genomes, including 308 herbarium specimens collected up to 190 years ago. In introduced European populations, we report selection signatures in defense genes and lower prevalence of particular plant pathogens in the invasive range. Together with temporal changes in population structure associated with introgression from closely related Ambrosia species, escape from microbial enemies likely favoured the plant’s remarkable success as an invasive species. One-Sentence Summary The invasive success of European ragweed was facilitated by release from enemy microbes and inter-species hybridization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| 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 teacher head, 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".