Genetic data facilitate research into a widespread and invasive cattail (Typha × glauca) hybrid zone in North America
Bibliographic record
Abstract
Genetic data can provide insights into the evolutionary ecology of hybrid zones and may be particularly important for investigating widespread and cryptic hybrids. In North America an expansive hybrid zone comprises the cattails Typha latifolia, T. angustifolia, and their hybrid T. × glauca. This hybrid is a problematic wetland invader that alters ecosystem functioning and reduces biodiversity. It is fertile and produces both backcrossed and advanced-generation hybrids, leading to morphological overlaps with parent species; therefore, genetic data are necessary for understanding the dynamics of this hybrid zone. In this review we summarize some of the ways in which genetic data have helped us to understand this hybrid zone, including the distributions of parent species and hybrids; symmetrical and asymmetrical hybrid crosses; the prevalence of different hybrid classes; hybrid fitness and hybrid breakdown; and gene flow and genetic diversity. We end by identifying some knowledge gaps and future research directions that can help us to further understand what may be the most widespread hybrid macrophyte in North America.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".