Species identification of North American guinea worms (Nematoda: <i>Dracunculus</i>) with DNA barcoding
Bibliographic record
Abstract
Dracunculus insignis is a nematode parasite that infects the subcutaneous tissues of mammals such as raccoon (Procyon lotor), mink (Neovison vison) and fisher (Martes pennanti). D. lutrae, a morphologically similar species, has only been recovered from the otter (Lontra canadensis). Species identification of these two North American guinea worms has only been achieved by morphology of males and host identity. As a result, where only female specimens are present, accurate identifications are not possible. To date, specimens recovered from otter have been assumed to be D. lutrae, while those from all other hosts are assumed to be D. insignis. This study uses DNA barcoding to differentiate between these two North American dracunculoids. Our results show that D. insignis is a 'true' generalist, showing little sequence divergence regardless of host association, although our studies did validate its occurrence in a new host - the otter. Interestingly, specimens of the host specialist, D. lutrae, showed some sequence divergence, although it was low. The finding of D. insignis in otter substantiates the need to supplement morphology-based methods in providing species identifications for certain dracunculoids.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 0.001 |
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".