DNA Barcoding of Commercially Important Salmon and Trout Species (Oncorhynchus and Salmo) from North America
Bibliographic record
Abstract
The present study investigated the ability of DNA barcoding to reliably identify the seven commercially important salmon and trout species (genera Oncorhynchus and Salmo ) in North America. More than 1000 salmonid reference samples were collected from a wide geographic range. DNA extracts from these samples were sequenced for the standard 650 bp barcode region of the cytochrome c oxidase subunit I gene (COI). DNA barcodes showed low intraspecies divergences (mean, 0.26%; range, 0.04-1.09%), and the mean congeneric divergence was 32-fold greater, at 8.22% (range, 3.42-12.67%). The minimum interspecies divergence was always greater than the maximum intraspecies divergence, indicating that these species can be reliably differentiated using DNA barcodes. Furthermore, several shorter barcode regions (109-218 bp), termed "mini-barcodes", were identified in silico that can differentiate all eight species, providing a potential means for species identification in heavily processed products.
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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 | 0.000 | 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 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".