Morphological and molecular characterization of <i>Quinqueserialis</i> (Digenea: Notocotylidae) species diversity in North America
Bibliographic record
Abstract
Estimates of trematode diversity are inaccurate due to unrecognized cryptic species and phenotypic plasticity within species. Integrative taxonomy (genetics, morphology and host use) increases the clarity of species delineation and improves knowledge of parasite biology. In this study, we used this approach to resolve taxonomic issues and test hypotheses of cryptic species in a genus of trematode, Quinqueserialis. Specimens from throughout North America were field collected from hosts and obtained from museums. We found three morphologically distinct groups and successfully sequenced specimens from two of these groups. DNA sequencing at the 28S and CO1 gene regions revealed that two of the three groups were genetically distinct. One genetic group included two morphological clusters demonstrating host-induced phenotypic plasticity within Quinqueserialis quinqueserialis. The other unique genetic group is a novel species, Quinqueserialis kinsellai n. sp., which is described herein. Our study illustrates the importance of integrating multiple sources of evidence when investigating trematode diversity to account for the influence of cryptic species or phenotypic plasticity. However, further sampling is needed to understand Quinqueserialis spp. diversity as some species have no genetic information associated with them.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".