Reconstruction of Biogeographic and Evolutionary Networks Using Reticulograms
Why this work is in the frame
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Bibliographic record
Abstract
A reticulogram is a general network capable of representing a reticulate evolutionary structure. It is particularly useful for portraying relationships among organisms that may be related in a nonunique way to their common ancestor - relationships that cannot be represented by a dendrogram or a phylogenetic tree. We propose a new method for constructing reticulograms that represent a given distance matrix. Reticulate evolution applies first to phylogenetic problems; it has been found in nature, for example, in the within-species microevolution of eukaryotes and in lateral gene transfer in bacteria. In this paper, we propose a new method for reconstructing reticulation networks and we develop applications of the reticulate evolution model to ecological biogeographic, population microevolutionary, and hybridization problems. The first example considers a spatially constrained reticulogram representing the postglacial dispersal of freshwater fishes in the Québec peninsula; the reticulogram provides a better model of postglacial dispersal than does a tree model. The second example depicts the morphological similarities among local populations of muskrats in a river valley in Belgium; adding supplementary branches to a tree depicting the river network leads to a better representation of the morphological distances among local populations of muskrats than does a tree structure. A third example involves hybrids between plants of the genus Aphelandra.
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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