Molecular identification of cetaceans from the West Atlantic using the E3-I5 region of COI
Bibliographic record
Abstract
Molecular identification is very useful in cases where morphology-based species identification is not possible. Examples for its application in cetaceans include the identification of carcasses of stranded animals in advanced state of decomposition and body parts that are illegally traded. One DNA region that is often used for molecular identification is the Folmer region of the mitochondrial gene cytochrome c oxidase subunit I (COI) (locus 48 to 705 bp). This locus has been used for the identification of several animal species, including whales and dolphins. The goal of the present study was to evaluate the usefulness of another region of COI, the E3-I5 (locus 685 to locus 1179; 495 bp) as a marker for identification of cetaceans from northeastern Canada and northeastern Brazil. The identification markers were successfully obtained for seven cetacean species after performing percent identity and Basic Local Alignment Search Tool analyses. The obtained markers are now publicly available and are useful for the identification of the endangered blue whale (Balaenoptera musculus), common minke whale (B. acutorostrata), vulnerable sperm whale (Physeter macrocephalus), harbor porpoise (Phocoena phocoena), common bottlenose dolphin (Tursiops truncatus), Guiana dolphin (Sotalia guianensis), and melon-headed whale (Peponocephala electra).
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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) | 0.001 | 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".