Hybridization between the threatened herb<i>Boltonia decurrens</i>(Asteraceae) and its widespread congener,<i>B. asteroides</i>
Bibliographic record
Abstract
Boltonia decurrens (Torr. & A. Gray) A. Wood is a federally threatened herb endemic to the Illinois River floodplain, and currently restricted to fewer than 25 populations. We tested for hybridization between this species and a widespread congener, Boltonia asteroides (L.) L’Hér., at two sites where they are known to occur in sympatry, by comparing morphological and genetic diversity with an allopatric population of each species. Morphological analyses identified significant differentiation between species. Discriminant classification analysis of the morphological data assigned most individuals to one or the other of the two parental species with high probability (>0.95), with only four plants having an intermediate probability of assignment (<0.90) indicative of hybrid origin. Similarly, likelihood-based methods based on genetic marker data (allozymes) failed to detect the presence of F1hybrids in either sympatric population and revealed only low frequencies of F2and backcross progeny. These findings demonstrate that combining morphological and genetic data increases the likelihood of detecting low-scale introgression between closely related species. Even with this combined approach, the low rate of recombination between these species together with their limited sympatry indicate that hybridization does not pose an immediate threat to the genetic integrity of B. decurrens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".