Extensive DNA Barcoding of Lepidoptera of Crete (Greece) Reveals Significant Taxonomic and Faunistic Gaps and Supports the First Comprehensive Checklist of the Island’s Fauna
Bibliographic record
Abstract
Comprehensive genetic surveys of Lepidoptera are still largely lacking across most of the eastern Mediterranean. Consequently, there is a lack of modern, taxonomically validated checklists that meet current scientific standards. In this study, we analyze the butterfly and moth fauna of Crete (Greece) for the first time, based on 3110 DNA barcode sequences, primarily obtained from specimens based on our own sampling program. Building on these data, and incorporating previously published records from print sources and online forums, we establish the first comprehensive checklist of the island's fauna. In total, the occurrence of 1230 species from 62 families is confirmed, with 724 of them genetically verified. Among them, 75 species appear to be island endemics. The checklist includes 125 newly recorded species for Crete, validated by DNA barcoding (with 36 also being new for Greece), along with 23 species confirmed solely through morphological study, and another 16 only documented by photographs. Conversely, 212 previously reported species had to be removed as likely invalid. Furthermore, 112 unidentified sequence clusters (BINs-Barcode Index Numbers) were documented, taxonomic uncertainties that will require future integrative resolution.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".