A complement to DNA barcoding reference library for identification of fish from the Northeast Pacific
Bibliographic record
Abstract
The seas of the North Pacific Ocean are characterized by a large variety of fish fauna, including endemic species. Molecular genetic methods, often based on DNA barcoding approaches, have been recently used to determine species boundaries and identify cryptic diversity within these species. This study complements the DNA barcode library of fish from the Northeast Pacific area. A library based on 154 sequences of the mitochondrial COI gene from 44 species was assembled and analyzed. It was found that 39 species (89%) can be unambiguously identified by the clear thresholds forming a barcoding gap. Deviations from the standard 2% threshold value resulted in detection of the species Enophrys lucasi in the sample, which is not typical for the eastern part of the Bering Sea. This barcoding gap also made it possible to identify naturally occurring low values of interspecific divergence of eulittoral taxa Aspidophoroides and the deep-sea genus Coryphaenoides. Synonymy of the genus Albatrossia in favor of the genus Coryphaenoides is suggested based on both the original and previously published data.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".