Taxonomy and phylogeny of the flowering plant genus Diervilla (Diervillaceae)
Bibliographic record
Abstract
My research consists of a taxonomic and phylogenetic analysis of the genus Diervilla (Bush honeysuckle), containing three eastern North American species, Diervilla lonicera, Diervilla rivularis, and Diervilla sessilifolia (Diervillaceae). Because there is a large amount of morphological variation found within each species, taxonomic boundaries are unclear. Diervilla lonicera has the largest coarse geographic range, which spans from the southern Appalachians to northeastern Canada. Diervilla sessilifolia and Diervilla rivularis are endemic to a few states in the southern Appalachians. My research has three main components: 1) a study of morphological variation and historical range information using herbarium specimens; 2) a multivariate ecological field study of all three species in the locations where their coarse ranges overlap in the southeastern United States; and 3) a phylogenetic analysis of multiple populations of the three species and their outgroup, Weigela. There was no evidence of the three taxa growing together across their range. The multivariate analysis results suggest that morphological data can be helpful to separate the taxa, but only on a small geographic scale. The environmental data from the ecological field study were inconclusive, with locality being the strongest factor. The phylogenetic analysis showed that the three taxa share a few derived genetic mutations, but overall, there is very little sequence variation. Based on my analyses, I cannot conclude that D. lonicera, D. sessilifolia, and D. rivularis are indeed three distinct taxa.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".