A new classification of<i>Carex</i>(Cyperaceae) subgenera supported by a HybSeq backbone phylogenetic tree
Bibliographic record
Abstract
Abstract The field of systematics is experiencing a new molecular revolution driven by the increased availability of high-throughput sequencing technologies. As these techniques become more affordable, the increased genomic resources have increasingly far-reaching implications for our understanding of the Tree of Life. With c. 2000 species, Carex (Cyperaceae) is one of the five largest genera of angiosperms and one of the two largest among monocots, but the phylogenetic relationships between the main lineages are still poorly understood. We designed a Cyperaceae-specific HybSeq bait kit using transcriptomic data of Carex siderosticta and Cyperus papyrus. We identified 554 low-copy nuclear orthologous loci, targeting a total length of c. 1 Mbp. Our Cyperaceae-specific kit shared loci with a recently published angiosperm-specific Anchored Hybrid Enrichment kit, which enabled us to include and compile data from different sources. We used our Cyperaceae kit to sequence 88 Carex spp., including samples of all the five major clades in the genus. For the first time, we present a phylogenetic tree of Carex based on hundreds of loci (308 nuclear exon matrices, 543 nuclear intron matrices and 66 plastid exon matrices), demonstrating that there are six strongly supported main lineages in Carex: the Siderostictae, Schoenoxiphium, Unispicate, Uncinia, Vignea and Core Carex clades. Based on our results, we suggest a revised subgeneric treatment and provide lists of the species belonging to each of the subgenera. Our results will inform future biogeographic, taxonomic, molecular dating and evolutionary studies in Carex and provide the step towards a revised classification that seems likely to stand the test of time.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".