DNA barcoding facilitates description of unknown faunas: a case study on Trichoptera in the headwaters of the Tigris River, Iraq
Bibliographic record
Abstract
Monitoring water quality with aquatic insects as sentinels requires taxonomic knowledge of adult and immature life stages that is not available in many parts of the world. We used deoxyribonucleic acid (DNA) barcoding to expedite identification of larval caddisflies from 20 sites in the headwaters of the Tigris River in northern Iraq by comparing their mitochondrial cytochrome c oxidase subunit I (COI) sequences to a global reference library (the Trichoptera Barcode of Life). We obtained full-length DNA barcodes for 16 COI haplogroups from 11 genera in 9 Trichoptera families. The most haplogroups and genera were recorded from Sulaimani Province. Two distinct COI haplogroups were found for the genus Psychomyia, and 5 haplogroups were found for Hydropsyche. The Hydropsyche COI haplogroups do not form a monophyletic clade with reference to the world fauna, but 4 out of 5 haplogroups are related to other Palearctic species. Three larval Rhyacophila specimens in a single COI haplogroup are closely related to specimens of Rhyacophila nubila Zetterstedt and Rhyacophila dorsalis (Curtis) from Europe, but adults from Iraq are needed to confirm their species identity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 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".