Incomplete reporting of whale, dolphin and porpoise ‘bycatch’ revealed by molecular monitoring of Korean markets
Bibliographic record
Abstract
Abstract We report the results of molecular monitoring of ‘whalemeat’ markets in the Republic of (South) Korea based on nine systematic surveys from February 2003 to February 2005. As Korea has no programme of commercial or scientific whaling and there is a closure on the hunting of dolphins and porpoises, the only legal source of these products was assumed to be incidental fisheries mortalities (‘bycatch’) as reported by the government to the International Whaling Commission. Species identification of 357 products using mitochondrial DNA control region or cytochrome b sequences and the web‐based programme DNA‐surveillance revealed three species of baleen whales (North Pacific minke, common form Bryde's and humpback), three species of beaked whales (Cuvier's, Stejneger's and Blainville's), seven species of dolphins (short‐finned pilot, false killer and killer whales; Risso's, bottlenose, common and Pacific white‐sided dolphins) and two species of porpoises (harbour and finless). Comparison of market products with official records revealed a number of discrepancies. Of the eight species identified on the markets in 2003, three were not reported in official records for that year. Of the 11 species identified in 2004, five were not reported as bycatch, although one species, a humpback whale, was reported as ‘stranded’. We also found significant inconsistencies in the expected frequencies of products from most species, including a large over‐representation of finless porpoises and false killer whales. We suggest ways in which market surveys could be improved to provide better information on the magnitude of fisheries bycatch and other illegal, unregulated and unreported (IUU) exploitation of wildlife.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".