Community engagement in seafood identification using DNA barcoding reveals market substitution in Canadian seafood
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Seafood authenticity is a global concern. As seafood consumption increases, so does public awareness of the associated nutritional and environmental issues related to seafood mislabeling. Cases of substitution continue to be observed, even after the adoption of DNA barcoding as a regulatory tool by the Food and Drug Administration in the United States in 2011. Although media coverage of these cases has highlighted the incidence of fraud in Canada, more in-depth engagement of the public is lacking. By partnering with community members to conduct research, knowledge about the incidence and impact of seafood mislabeling can be directly communicated to consumers. In this study high school students and educators participated in a market survey using DNA barcoding to identify seafood. The Canadian Food Inspection Agency Fish List was used to determine if mislabeling had occurred. Twenty-three percent of samples surveyed were mislabeled, suggesting that the incidence of retail seafood mislabeling continues to be significant in Canada. Continued involvement of the public in market surveys will help to monitor trends in seafood mislabeling, and may help to increase awareness of potential seafood fraud.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it