Problematic barcoding in flatworms: A case-study on monogeneans and rhabdocoels (Platyhelminthes)
Bibliographic record
Abstract
Some taxonomic groups are less amenable to mitochondrial DNA barcoding than others. Due to the paucity of molecular information of understudied groups and the huge molecular diversity within flatworms, primer design has been hampered. Indeed, all attempts to develop universal flatworm-specific COI markers have failed so far. We demonstrate how high molecular variability and contamination problems limit the possibilities for barcoding using standard COI-based protocols in flatworms. As a consequence, molecular identification methods often rely on other widely applicable markers. In the case of Monogenea, a very diverse group of platyhelminth parasites, and Rhabdocoela, representing one-fourth of all free-living flatworm taxa, this has led to a relatively high availability of nuclear ITS and 18S/28S rDNA sequences on GenBank. In a comparison of the effectiveness in species assignment we conclude that mitochondrial and nuclear ribosomal markers perform equally well. In case intraspecific information is needed, rDNA sequences can guide the selection of the appropriate (i.e. taxon-specific) COI primers if available.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".