Overlooked diversity in exotic <i>Taraxacum</i> in British Columbia, Canada
Bibliographic record
Abstract
In almost all North American literature, including in British Columbia, weedy Taraxacum species have been named as Taraxacum officinale F.H.Wigg and Taraxacum erythrospermum Andrz. ex Besser (or Taraxacum laevigatum DC.). This coarse taxonomic approach ignores great diversity in morphology, ecology, and geographical distributions among the exotic established species. Taxonomic refinement would facilitate floristics and ecological studies when exotic Taraxacum species are involved, and the taxonomy of native Taraxacum must first determine which are and which are not native species, which in turn requires knowledge of sectional identity of any specimen. Exotic Taraxacum specimens were identified to species and taxonomic sections using refined species and sectional concepts that align with taxonomic standards used in the native ranges of the species in Europe. Seven exotic sections and one informally named group are found to be present in British Columbia (Borea, Boreigena, Celtica, Erythrosperma, Hamata, Naevosa, Taraxacum, and the Taraxacum fulvicarpum group). The number of exotic Taraxacum species known to occur in British Columbia to date exceeds 100. A key to the exotic sections of British Columbia Taraxacum is presented and the sections are characterized. Species known to date are listed by their sectional placement. Notes are also presented on distinguishing native from exotic Taraxacum in British Columbia.
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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 | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".