Genetic Relationships among species of Populus (Salicaceae) based on nuclear genomic data<sup>1</sup>
Bibliographic record
Abstract
The genus Populus comprises some of the most commercially exploited, pioneer forest trees distributed throughout the northern-hemisphere. The high level of morphological diversity, extensive inter-species hybridization, and low level of DNA sequence variation among species in this group have impeded the progress of taxonomic and phylogenetic studies. We used nuclear genomic data based upon inter simple sequence repeat (ISSR) variability, a highly variable class of molecular markers to determine the genetic relationships among species of the genus Populus. Species of the section Populus (Leuce) clustered together suggesting monophyly of the section Populus. The Eurasian members of section Populus (P. alba, P. davidiana, and P. tremula) showed closer genetic relationships to each other than to two North American aspens (P. tremuloides and P. grandidentata) of the same section. In contrast to previous phylogenetic studies, P. nigra showed a close genetic relationship to species of the section Tacamahaca. This relationship is in agreement with various phenotypic traits, interfertility and chemistry of bud exudates and serves as evidence for introgression between P. nigra and species of the section Tacamahaca. Overall, the genetic relatedness estimates based on nuclear ISSR data were congruent with phylogenetic trees based on other molecular (RFLP and DNA sequence) and morphological data, but provided better resolution in assessing the genetic relatedness among closely related taxa, and provided genetic evidence for previously suspected introgressions.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".