DNA barcode analysis of butterfly species from<scp>P</scp>akistan points towards regional endemism
Bibliographic record
Abstract
DNA barcodes were obtained for 81 butterfly species belonging to 52 genera from sites in north-central Pakistan to test the utility of barcoding for their identification and to gain a better understanding of regional barcode variation. These species represent 25% of the butterfly fauna of Pakistan and belong to five families, although the Nymphalidae were dominant, comprising 38% of the total specimens. Barcode analysis showed that maximum conspecific divergence was 1.6%, while there was 1.7-14.3% divergence from the nearest neighbour species. Barcode records for 55 species showed <2% sequence divergence to records in the Barcode of Life Data Systems (BOLD), but only 26 of these cases involved specimens from neighbouring India and Central Asia. Analysis revealed that most species showed little incremental sequence variation when specimens from other regions were considered, but a threefold increase was noted in a few cases. There was a clear gap between maximum intraspecific and minimum nearest neighbour distance for all 81 species. Neighbour-joining cluster analysis showed that members of each species formed a monophyletic cluster with strong bootstrap support. The barcode results revealed two provisional species that could not be clearly linked to known taxa, while 24 other species gained their first coverage. Future work should extend the barcode reference library to include all butterfly species from Pakistan as well as neighbouring countries to gain a better understanding of regional variation in barcode sequences in this topographically and climatically complex region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".