Reassessment of the phylogenetic relationships among Anodonta, Pyganodon, and Utterbackia (Bivalvia: Unionoida) using mutation coding of allozyme data
Bibliographic record
Abstract
The use of molecular markers has greatly increased our understanding of unionoid systematics. However, it is critical that their use in phylogenetic studies be conducted with the correct methodologies in order to ensure that the correct interpretations of evolutionary history are made. The phylogenetic relationships of a selection of Anodonta were investigated by Hoeh (1990), who found variation in 23 allozyme loci. These allozymes were coded using the presence/absence of alleles, yielding 67 characters used in a phylogenetic analysis. The resulting phylogeny was used as evidence to recommend the elevation of Pyganodon and Utterbackia to full generic status. Since the publication of Hoeh (1990) the coding of characters using the presence/absence of alleles has been shown to be invalid and has been superseded by mutation coding, with the locus as the character. The phylogenetic analysis of 20 characters, coded using mutation coding, yielded two equally parsimonious trees and an interpretation markedly different from that of Hoeh (1990). Both trees supported the monophyly of Pyganodon and Utterbackia. However, the genus Anodonta was paraphyletic with respect to both Pyganodon and Utterbackia. The one Eurasian species (Anodonta cygnea) was resolved as the sister of the remaining ingroup taxa, including Pyganodon, Utterbackia, and the North American Anodonta. These findings lead to a taxonomic problem, requiring further phylogenetic analysis of the Anodontinae. In order to test the phylogenetic hypotheses presented herein, we strongly recommend the construction of a phylogeny for all anodontine taxa using a combination of mitochondrial and nuclear DNA sequences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".