Towards a comprehensive barcode library for arctic life - Ephemeroptera, Plecoptera, and Trichoptera of Churchill, Manitoba, Canada
Bibliographic record
Abstract
BACKGROUND: This study reports progress in assembling a DNA barcode reference library for Ephemeroptera, Plecoptera, and Trichoptera ("EPTs") from a Canadian subarctic site, which is the focus of a comprehensive biodiversity inventory using DNA barcoding. These three groups of aquatic insects exhibit a moderate level of species diversity, making them ideal for testing the feasibility of DNA barcoding for routine biotic surveys. We explore the correlation between the morphological species delineations, DNA barcode-based haplotype clusters delimited by a sequence threshold (2%), and a threshold-free approach to biodiversity quantification--phylogenetic diversity. RESULTS: A DNA barcode reference library is built for 112 EPT species for the focal region, consisting of 2277 COI sequences. Close correspondence was found between EPT morphospecies and haplotype clusters as designated using a standard threshold value. Similarly, the shapes of taxon accumulation curves based upon haplotype clusters were very similar to those generated using phylogenetic diversity accumulation curves, but were much more computationally efficient. CONCLUSION: The results of this study will facilitate other lines of research on northern EPTs and also bode well for rapidly conducting initial biodiversity assessments in unknown EPT faunas.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".