First Distributional Study of Branchiobdellida (Annelida: Clitellata) in the Great Smoky Mountains National Park, North Carolina and Tennessee, USA, with a Redescription of<i>Cambarincola holostomus</i>Hoffman, 1963
Bibliographic record
Abstract
Branchiobdellidans, or crayfish worms, are species-rich in the Appalachian area of the southeastern United States. Even so, the Great Smoky Mountains National Park (GSMNP) in the southern Appalachians has only one record of a branchiobdellidan species. As part of the All Taxa Biodiversity Inventory, we undertook a general survey of the branchiobdellidans in the GSMNP. Crayfish were collected from a total of 15 sites distributed across 11 watersheds in the GSMNP We identified a total of 10 species of branchiobdellidans: 1 species of Bdellodrilus, 1 species of Oedipodrilus, 2 species of Pterodrilus, 1 species of Xironodrilus, and 5 species of Cambarincola. The composition and number of species per site ranged from 0 to 6, and individual branchiobdellidan species occurrence ranged from 1 to 11 sites. Our results suggest that multiple factors affect distribution and occurrence on certain hosts. Study of specimens of Cambarincola holostomus Hoffman, 1963 enabled us to add new morphological characters to the description of this species. An intensive survey of watersheds and crayfish fauna in the GSMNP is necessary to understand the multiple factors affecting species distributions and host preferences and to facilitate conservation of both the symbionts and their hosts.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".