Molecular diversity and species delimitation in the family Gasteruptiidae (Hymenoptera: Evanioidea)
Bibliographic record
Abstract
Gasteruptiidae Ashmead is an easily recognised family of wasps with ∼589 described species worldwide. Although well characterised by traditional taxonomy, multiple authors have commented on the extreme morphological uniformity of the group, making species-level identification difficult. This problem is enhanced by the lack of molecular data and molecular phylogenetic research for the group. We used 187 cytochrome c oxidase subunit I (COI) barcodes to explore the efficiency of sequence data to delimitate species in Gasteruptiidae. We undertook a graphical and discussion-based comparison of six methods for species delimitation, with the success of methods judged based on known species boundaries and morphology. Both distance-based (ABGD and jMOTU threshold analysis) and tree-based (GMYC and PTP) methods compared across multiple parameters recovered variable molecular operational taxonomic units (MOTUs), ranging from 55 to 123 MOTUs. Tree-based methods tended to split known morphological species less than distance-based methods, with the single-threshold GMYC method the most concordant with known morphospecies. Our results suggest that the incorporation of molecular species delimitation techniques provides a powerful tool to assist in the interpretation of species and help direct informed decisions with taxonomic uncertainty in the family.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".