Cryptic lineages and hybridization in freshwater mussels of the genus Pyganodon (Unionidae) in northeastern North America
Bibliographic record
Abstract
The distribution of freshwater mussels Pyganodon Crosse and P. Fischer, 1894 traditionally inferred from morphological characters was validated by a genetic characterization of the genus within the Quebec peninsula. Individuals were identified by comparing the sequences from the female mitochondrial genome (COI and 16S) with those of reference individuals, while hybridization was assessed with male mitochondrial (COI and COII) and nuclear genomes (ITS1 and ITS2). The results confirmed most of the previous morphological identifications but revealed unexpected results. Both male and female mitochondrial genomes support the distinction between Pyganodon fragilis (Lamarck, 1819) and Pyganodon cataracta (Say, 1817). However, only one lineage of Pyganodon grandis (Say, 1829), instead of the two expected, was detected in the sampled area. The genetic survey also revealed the presence of two unidentified Pyganodon lineages, previously unreported within the Quebec peninsula. These extremely rare lineages harbour the signature of ancestral hybridizations. Finally, recent divergence and hybridizations make shell characters only partially efficient in discriminating Pyganodon lineages.
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 | 0.000 | 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 | 0.001 | 0.001 |
| 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".