A Taxonomic Revision of Echinacea (Asteraceae: Heliantheae)
Bibliographic record
Abstract
Abstract A morphometric analysis was conducted of Echinacea Moench (Asteraceae) to measure variation between native populations for taxonomic purposes. Data were collected from living and herbarium specimens. From a matrix of 321 specimens by 74 characters, a pair-wise distance matrix was computed using Gower's coefficient. Cluster strategies were explored from the distance matrix. MODECLUS clustering separated the data into two clusters, and a flexible agglomerative clustering method separated the data into the same two clusters, which were broken into four sub-clusters. Canonical discriminant analysis gave significant support for the two- and the four-cluster solutions. Canonical discriminant analysis also showed support for eight smaller clusters identified using McGregor's 1968 classification. We recognize two subgenera and four species: Echinacea subg. Echinacea contains only E. purpurea; Echinacea subg. Pallida contains E. atrorubens, E. laevigata, and E. pallida. The revised varieties are as follows: E. atrorubens var. atrorubens, E. atrorubens var. neglecta, E. atrorubens var. paradoxa, E. pallida var. angustifolia, E. pallida var. pallida, E. pallida var. sanguinea, E. pallida var. simulata, and E. pallida var. tennesseensis. A cladistic analysis was done on the four species. In the most parsimonious solution, E. purpurea was basally divergent to a clade of the other three species (70% bootstrap value), and all four were distinguishable by at least one apomorphy. A key to Echinacea taxa is provided, which should be valuable given the pharmaceutical and horticultural importance of Echinacea. Communicating Editor: Paul Wilson
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 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".