Identifying the last supper: utility of the DNA barcode library for bloodmeal identification in ticks
Bibliographic record
Abstract
Ticks are among the most important vectors of disease in the Northern Hemisphere, and a better understanding of their feeding behaviour and life cycle is critical to the management and control of tick-borne zoonoses. DNA-based tools for the identification of residual bloodmeals in hematophagous arthropods have proven useful in the investigation of patterns of host use in nature. Using a blind test approach, we challenged the utility of the DNA barcode library for the identification of vertebrate bloodmeals in engorged, field-collected Ixodes scapularis. Universal vertebrate primers for the COI barcode region successfully amplified DNA from the host bloodmeal and only rarely amplified tick DNA. Of the 61 field-collected ticks, conclusive genus- and species-level identification was possible for 72% of the specimens. In all but two cases, barcode-based identification of the bloodmeal was consistent with the morphological identification of the vertebrate host the ticks were collected from. Possible explanations for mismatches or ambiguities are presented. This study validates the utility of the DNA barcode library as a valuable and reliable resource for the identification of unknown bloodmeals in arthropod vectors of disease. Future directions aimed at the refinement of these techniques to gain additional information and to improve the amplification success of digested vertebrate DNA in tick bloodmeals are discussed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".