DNA Barcoding of Mosquitoes from the Pantanos de Centla Biosphere Reserve, Southeastern Mexico
Bibliographic record
Abstract
Accurate identification of mosquito species is essential to support programs that involve the study of distribution and mosquito control. Numerous mosquito species are difficult to identify based only on morphological characteristics, due to the morphological similarities in different life stages and large numbers of some species that are members of morphologically similar species complexes. In the present study, the mosquitoes collected in the Pantanos de Centla Biosphere Reserve, southeastern Mexico, were evaluated using a combination of morphological and molecular approaches (mitochondrial cytochrome c oxidase subunit I [COI] DNA barcode). A total of 1,576 specimens of 10 genera and 35 species, mostly adult stages, were collected. A total of 225 COI DNA barcode sequences were analyzed; most species formed well-supported groups in the neighbor joining, maximum likelihood, and Bayesian inference trees. The intraspecific Kimura 2-parameter (K2P) genetic distance averaged 1.52%. An intraspecific K2P distance of 6.20% was observed in Anopheles crucians s.l., while a deep split was identified in Culex erraticus and Cx. conspirator. This study showed that COI DNA barcodes offer a reliable approach to support mosquito species identification in Mexico.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 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".