Enhancing DNA barcode reference libraries by harvesting terrestrial arthropods at the Smithsonian's National Museum of Natural History
Why this work is in the frame
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Bibliographic record
Abstract
The use of DNA barcoding has revolutionised biodiversity science, but its application depends on the existence of comprehensive and reliable reference libraries. For many poorly known taxa, such reference sequences are missing even at higher-level taxonomic scales. We harvested the collections of the Smithsonian's National Museum of Natural History (USNM) to generate DNA barcoding sequences for genera of terrestrial arthropods previously not recorded in one or more major public sequence databases. Our workflow used a mix of Sanger and Next-Generation Sequencing (NGS) approaches to maximise sequence recovery while ensuring affordable cost. In total, COI sequences were obtained for 5,686 specimens belonging to 3,737 determined species in 3,886 genera and 205 families distributed in 137 countries. Success rates varied widely according to collection data and focal taxon. NGS helped recover sequences of specimens that failed a previous run of Sanger sequencing. Success rates and the optimal balance between Sanger and NGS are the most important drivers to maximise output and minimise cost in future projects. The corresponding sequence and taxonomic data can be accessed through the Barcode of Life Data System, GenBank, the Global Biodiversity Information Facility, the Global Genome Biodiversity Network Data Portal and the NMNH data portal.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 it