DNA barcoding of forensically important flies in the Western Cape, South Africa
Bibliographic record
Abstract
Forensic entomology aids the determination of post mortem interval based on arthropods associated with a deceased body. This relies on the accurate identification of insects that visit the body, particularly first colonisers such as Calliphoridae (Diptera). Traditional species identification though morphological keys can be challenging as immature or closely related specimens can look similar. Some of these challenges have been overcome through "DNA barcoding", which involves the sequencing of informative regions within a species' DNA and comparison to a database of reference sequences. However, reference DNA sequences of blow fly species in South Africa is currently limited. In this study, adult blow flies representing four species common to the Western Cape, South Africa (Chrysomya chloropyga, Chrysomya albiceps, Chrysomya marginalis, Lucilia sericata) were examined using morphological keys and DNA barcoding of two regions: COI and ITS2. These DNA sequences were then used as references for the successful identification of seven unknown immature specimens. Intraspecific divergence showed a maximum of 0.36% and 2.25% for COI and ITS2, respectively; interspecific divergence showed a minimum of 6.14% and 64.6% for COI and ITS2, respectively. According to these results, COI and ITS2 have sufficient discriminatory power for species-level identification for the four species studied.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".