Integrating DNA barcodes and morphology for species delimitation in the<i>Corynoneura</i>group (Diptera: Chironomidae: Orthocladiinae)
Bibliographic record
Abstract
In this study, we use DNA barcodes for species delimitation to solve taxonomic conflicts in 86 specimens of 14 species belonging to the Corynoneura group (Diptera: Chironomidae: Orthocladiinae), from the Atlantic Forest, Brazil. Molecular analysis of cytochrome c-oxidase subunit I (COI) gene sequences supported 14 cohesive species groups, of which two similar groups were subsequently associated with morphological variation at the pupal stage. Eleven species previously described based on morphological criteria were linked to DNA markers. Furthermore, there is the possibility that there may be cryptic species within the Corynoneura group, since one group of species presented internal grouping, although no morphological divergence was observed. Our results support DNA-barcoding as an excellent tool for species delimitation in groups where taxonomy by means of morphology is difficult or even impossible.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".