Perspectives on the reclassification of taxa in the <i>Arceuthobium campylopodum</i> complex (Viscaceae)
Bibliographic record
Abstract
The taxonomic classification of dwarf mistletoes ( Arceuthobium spp., Viscaceae) in series Campylopoda requires a multi-trait approach, integrating plant genetics, morphologies, and phenologies as well as their host and geographic distributions. Thus, competing interpretations on the contribution of these traits to defining species and subspecies boundaries has spurred considerable debate. Accordingly, the recent reclassification of 12 previously recognized species in ser. Campylopoda to separate subspecies of Arceuthobium campylopodum in the Flora of North America (FNA) has furthered this debate. We contend that these taxa deserve separate species recognition, while subspecies described prior to and after the recombination of ser. Campylopoda taxa in the FNA also deserve recognition. Herein, we provide evidence that the treatment in the FNA does not adequately reflect the diverse morphological, geographic, host, and phenological differences across the series, and hence, we maintain that the reclassification of ser. Campylopoda taxa was not justified according to empirical evidence published prior to and following the FNA treatment. We conclude our critique of the FNA treatment of ser. Campylopoda by advocating for the continued application of the Hawksworth and Wiens’ classification system, with minor modifications to the constitution of the series.
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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 | 0.037 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".