DNA barcoding and the taxonomy of <scp>M</scp>icrogastrinae wasps (<scp>H</scp>ymenoptera, <scp>B</scp>raconidae): impacts after 8 years and nearly 20 000 sequences
Bibliographic record
Abstract
Microgastrine wasps are among the most species-rich and numerous parasitoids of caterpillars (Lepidoptera). They are often host-specific and thus are extensively used in biological control efforts and figure prominently in trophic webs. However, their extraordinary diversity coupled with the occurrence of many cryptic species produces a significant taxonomic impediment. We present and release the results of 8 years (2004-2011) of DNA barcoding microgastrine wasps. Currently they are the best represented group of parasitoid Hymenoptera in the Barcode of Life Data System (BOLD), a massive barcode storage and analysis data management site for the International Barcoding of Life (iBOL) program. There are records from more than 20 000 specimens from 75 countries, including 50 genera (90% of the known total) and more than 1700 species (as indicated by Barcode Index Numbers and 2% MOTU). We briefly discuss the importance of this DNA data set and its collateral information for future research in: (1) discovery of cryptic species and description of new taxa; (2) estimating species numbers in biodiversity inventories; (3) clarification of generic boundaries; (4) biological control programmes; (5) molecular studies of host-parasitoid biology and ecology; (6) evaluation of shifts in species distribution and phenology; and (7) fostering collaboration at national, regional and world levels. The integration of DNA barcoding with traditional morphology-based taxonomy, host records, and other data has substantially improved the accuracy of microgastrine wasp identifications and will significantly accelerate further studies on this group of parasitoids.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".