Defining entities in the Acacia saligna (Fabaceae) species complex using a population genetics approach
Why this work is in the frame
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Bibliographic record
Abstract
Traditional morphological taxonomic classification is problematic in the Acacia saligna (Labill.) H.L.Wendl. species complex. Reliable identification of entities within the species is essential due to its extensive use both in Australia and overseas, its propensity for weediness, and its ongoing development for use in agroforestry. We used a Bayesian analysis approach to assess genetic structure in populations across the species natural range and to define the natural distributions of various genetic entities. The results indicate that three highly divergent genetic entities are apparent in the A. saligna species complex with further fine-scale genetic subdivision present within two. The three primary genetic entities correspond to the informally described subsp. ‘saligna’ and subsp. ‘pruinescens’ combined, subsp. ‘stolonifera’, and subsp. ‘lindleyi’. Within this primary structure two further entities are apparent; one separating subsp. ‘saligna’/‘pruinescens’ into eastern and western populations and the other distinguishing north-western ‘lindleyi’ populations from the rest of that subspecies distribution. The north-western catchments may have been an important refugium for the species diversity. The results of the study will aid in breeding programs, conservation of natural populations and control of invasive populations of this taxon.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it