Review of the North American fauna of Drymeia Meigen (Diptera, Muscidae) and evaluation of DNA barcodes for species-level identification in the genus
Bibliographic record
Abstract
The North American fauna of Drymeia Meigen was studied. Four new species are described (Drymeia huckettisp. nov., Drymeia pontisp. nov., Drymeia vockerothisp. nov., Drymeia woodorumsp. nov.), and three new synonymies are proposed: Drymeia amnicola (Huckett, 1966) (= Drymeia rivalis (Huckett, 1966), syn. nov.); Drymeia glacialis (Rondani, 1866) (= Drymeia alpicola (Rondani, 1871), syn. nov.); and Drymeia spinitarsis (Aldrich, 1918) (= Drymeia longiseta Sorokina & Pont, 2015, syn. nov.). An annotated checklist, DNA barcodes (when available), and keys for each sex of the 24 named species of North American Drymeia are provided. The utility of DNA barcodes for the identification of Drymeia species across a wide geographical range was explored using sequences from five countries. A match between morphology and DNA barcodes was found for 71% (22/31) of species studied (including three unnamed taxa). The remaining nine species clustered into two groups of taxa with very little interspecific variation within clusters (groups of two and seven species). Caution is advised against using DNA barcoding as the only determination tool for Drymeia material without prior knowledge of its limitations for certain species groups.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| 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) | 0.002 | 0.001 |
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".