Biological identifications through DNA barcodes: the case of the Crustacea
Bibliographic record
Abstract
The ability of a 650 base pair section of the mitochondrial cytochrome c oxidase I (COI) gene to provide species-level identifications has been demonstrated for large taxonomic assemblages of animals such as insects, birds, and fishes, but not for the subphylum Crustacea, one of the most diverse groups of arthropods. In this study, we test the ability of COI to provide identifications in this group, examining two disparate levels in the taxonomic hierarchy — orders and species. The first phase of our study involved the development of a sequence profile for 23 dominant crustacean orders, based upon the analysis of 150 species, each belonging to a different family. The COI amino acid data placed these taxa into cohesive assemblages whose membership coincided with currently accepted boundaries at the order, superorder, and subclass levels. Species-level resolution was subsequently examined in an assemblage of Decapoda and in representatives of the genera Daphnia (Cladocera) and Gammarus (Amphipoda). These studies revealed that levels of nucleotide sequence divergence were from 19 to 48 times greater between congeneric species than between individuals of a species. We conclude that sequence variation in the COI barcode region will be very effective for discriminating species of Crustacea.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".