Phylogenetic analysis of the genus Paratanytarsus (Diptera: Chironomidae)
Bibliographic record
Abstract
The non-biting midges (Chironomidae) are among of the most successful insects in freshwater systems and often dominate in abundance and species richness. The genus Paratanytarsus contains species from all biogeographic regions except tropical Africa, 19 species are known from Europe. Previous molecular work has suggested the presence of undescribed species within some species groups, in addition the monophyly of the genus has been questioned. In this study four nuclear molecular markers, CAD1, CAD4, PGD and AATS1 are utilized in order to reconstruct the evolutionary history of the genus. Samples identified to 16 different species have been collected at locations in Northern Europe, Arctic Canada and Australia. The results of the phylogenetic analysis supports the monophyly of the genus, while considerable intraspesific variation is revealed within several species. Material identified to P. austriacus/hyperboreus is found to group into four separated genetic clusters, two of which appear to be undescribed cryptic species based on currently used morphological characters. Canadian P. dissimilis and P. tenuis ends up paraphyletic with respect to European samples and might represent new Nearctic species. The Australian taxa came out well-embedded in the tree without any close relatives. It is hypothesized that bipolar migrations has occurred in the history of the genus.
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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 | 0.001 |
| 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".