DNA barcodes enable higher taxonomic assignments in the Acari
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although mites (Acari) are abundant in many terrestrial and freshwater ecosystems, their diversity is poorly understood. Since most mite species can be distinguished by variation in the DNA barcode region of cytochrome c oxidase I, the Barcode Index Number (BIN) system provides a reliable species proxy that facilitates large-scale surveys. Such analysis reveals many new BINs that can only be identified as Acari until they are examined by a taxonomic specialist. This study demonstrates that the Barcode of Life Datasystem's identification engine (BOLD ID) generally delivers correct ordinal and family assignments from both full-length DNA barcodes and their truncated versions gathered in metabarcoding studies. This result was demonstrated by examining BOLD ID's capacity to assign 7021 mite BINs to their correct order (4) and family (189). Identification success improved with sequence length and taxon coverage but varied among orders indicating the need for lineage-specific thresholds. A strict sequence similarity threshold (86.6%) prevented all ordinal misassignments and allowed the identification of 78.6% of the 7021 BINs. However, higher thresholds were required to eliminate family misassignments for Sarcoptiformes (89.9%), and Trombidiformes (91.4%), consequently reducing the proportion of BINs identified to 68.6%. Lineages with low barcode coverage in the reference library should be prioritized for barcode library expansion to improve assignment success.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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