Evolutionary history of <i>Magnolia</i> sect. <i>Talauma</i> (Magnoliaceae) in Cuba
Bibliographic record
Abstract
Abstract Evolutionary biologists recognize that understanding the phylogenetic history of closely related species is challenging without considering their population genetics history. The taxonomy of Magnolia sect. Talauma in Cuba has long been debated, with several changes in taxon delimitations. All these taxonomic revisions were based exclusively on leaf morphological characteristics of a few individuals, limiting their ability to elucidate taxon boundaries. Recent studies have focused on conservation genetics and species delimitation of Cuban magnolias, based on ecological, morphological and genetic data. Here, we use full plastome sequences and microsatellite data to infer phylogenetic relationships and potential historical migration events among species in Magnolia sect. Talauma in Cuba. Bayesian phylogeny and TreeMix were used to understand the phylogenetic relationships. Based on this, Magnolia sect. Talauma in Cuba does not comprise a monophyletic group. The data continue to show a highly supported unresolved species complex in the taxa of Magnolia subsect. Talauma from north-eastern Cuba. From a taxonomic point of view, our results do not entirely support the most recent taxonomic review proposed for the family in Cuba.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".