Recent evolution of ancient Arctic leech relatives: systematics of Acanthobdellida
Bibliographic record
Abstract
Abstract Acanthobdellida gnaw into the sides of salmonid fishes in frigid Arctic lakes and rivers, latching on with fearsome facial hooks. Sister to leeches, they are an ancient lineage with two described species. Unfortunately, Acanthobdellida are rarely collected, leading to a paucity of literature despite their unique morphology. Populations range from Eurasia to Alaska (USA), but few specimens of Acanthobdella peledina are represented in molecular studies, and no molecular data exist for Paracanthobdella livanowi, making their taxonomic position difficult to assess. We use phylogenetics and morphology to determine whether allopatric populations of A. peledina are distinct species and assess the current classification scheme used for Acanthobdellida. We produce a new suborder, Acanthobdelliformes, to match the taxonomy within Hirudinea. Scanning electron micrographs indicate species-level differences in the anterior sucker and facial hooks; molecular phylogenetics mirrors this divergence between species. We assign both species to the family Acanthobdellidae and abandon the family Paracanthobdellidae. Alaskan and European A. peledina populations are morphologically similar, but appear phylogenetically divergent. Our data strongly suggest that members of the order Acanthobdellida diverged relatively recently in their ancient history, but based on genetic distance, this divergence appears to pre-date the most recent cycles of glaciation.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".