A bi‐organellar phylogenomic study of Pandanales: inference of higher‐order relationships and unusual rate‐variation patterns
Bibliographic record
Abstract
We used a bi-organellar phylogenomic approach to address higher-order relationships in Pandanales, including the first molecular phylogenetic study of the panama-hat family, Cyclanthaceae. Our genus-level study of plastid and mitochondrial gene sets includes a comprehensive sampling of photosynthetic lineages across the order, and provides a framework for investigating clade ages, biogeographic hypotheses and organellar molecular evolution. Using multiple inference methods and both organellar genomes, we recovered mostly congruent and strongly supported relationships within and between families, including the placement of fully mycoheterotrophic Triuridaceae. Cyclanthaceae and Pandanaceae plastomes have slow substitution rates, contributing to weakly supported plastid-based relationships in Cyclanthaceae. While generally slowly evolving, mitochondrial genomes exhibit sporadic rate elevation across the order. However, we infer well-supported relationships even for slower evolving mitochondrial lineages in Cyclanthaceae. Clade age estimates across photosynthetic lineages are largely consistent with previous studies, are well correlated between the two organellar genomes (with slightly younger inferences from mitochondrial data), and support several biogeographic hypotheses. We show that rapidly evolving non-photosynthetic lineages may bias age estimates upwards at neighbouring photosynthetic nodes, even using a relaxed clock model. Finally, we uncovered new genome structural variants in photosynthetic taxa at plastid inverted repeat boundaries that show promise as interfamilial phylogenetic markers.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".