Linking morphological and molecular taxonomy for the identification of poultry house, soil, and nest dwelling mites in the Western Palearctic
Bibliographic record
Abstract
Because of its ability to expedite specimen identification and species delineation, the barcode index number (BIN) system presents a powerful tool to characterize hyperdiverse invertebrate groups such as the Acari (mites). However, the congruence between BINs and morphologically recognized species has seen limited testing in this taxon. We therefore apply this method towards the development of a barcode reference library for soil, poultry litter, and nest dwelling mites in the Western Palearctic. Through analysis of over 600 specimens, we provide DNA barcode coverage for 35 described species and 70 molecular taxonomic units (BINs). Nearly 80% of the species were accurately identified through this method, but just 60% perfectly matched (1:1) with BINs. High intraspecific divergences were found in 34% of the species examined and likely reflect cryptic diversity, highlighting the need for revision in these taxa. These findings provide a valuable resource for integrative pest management, but also highlight the importance of integrating morphological and molecular methods for fine-scale taxonomic resolution in poorly-known invertebrate lineages.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".