DNA barcode library for European Gelechiidae (Lepidoptera) suggests greatly underestimated species diversity
Bibliographic record
Abstract
oxidase 1) from 751 out of 865 nominal species, belonging to 105 genera, were successfully recovered. A total of 741 species represented by specimens with sequences ≥ 500bp and an additional ten species represented by specimens with shorter sequences were used to produce 53 NJ trees. Intraspecific barcode divergence averaged only 0.54% whereas distance to the Nearest-Neighbour species averaged 5.58%. Of these, 710 species possessed unique DNA barcodes, but 31 species could not be reliably discriminated because of barcode sharing or partial barcode overlap. Species discrimination based on the Barcode Index System (BIN) was successful for 668 out of 723 species which clustered from minimum one to maximum 22 unique BINs. Fifty-five species shared a BIN with up to four species and identification from DNA barcode data is uncertain. Finally, 65 clusters with a unique BIN remained unidentified to species level. These putative taxa, as well as 114 nominal species with more than one BIN, suggest the presence of considerable cryptic diversity, cases which should be examined in future revisionary studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".