Development and Validation of Protocols To Differentiate PCB Patterns between Farmed and Wild Salmon
Bibliographic record
Abstract
Polychlorinated biphenyl (PCB) congener patterns based on full congener PCB analyses of three farmed and five wild species of salmon from coastal British Columbia, Canada are compared using principal components analysis (PCA) and the best fit linear decomposition of the observed PCB composition in terms of Aroclor 1242, 1254, and 1260 end-members. The two complementary analysis methods are used to investigate congener composition pattern differences between species, trophic levels, feeding preferences, and farmed or wild feeding regimes, with the intent of better understanding PCB processes in both salmon and salmon consumers. PCA supports classification of PCB congeners into nine groups based on a) structure activity groups (SAG) related to the bioaccumulation potential in fish-eating mammals, b) Cl number, and c) the numbers of vicinal meta- and para-H. All three factors are needed to interpret congener distributions since SAGs by themselves do not fully explain PCB distributions. Farmed salmon exhibit very similar congener patterns that overlap the PCA and Aroclor composition of their food, while wild salmon separate into two distinct groups, with chinook and "coastal" coho having higher proportions of the higher chlorinated, Aroclor 1260 type, nonmetabolizable congeners, and chum, pink, sockeye, and "remote" coho having higher proportions of the lower chlorinated, more volatile and metabolizable Aroclor 1242 type, congeners. Wild chinook have the highest PCB and toxic equivalent (TEQ) concentrations, and the highest proportions of A1254 A1260, and PCB congeners in the most refractory SAG. Because both "coastal" and "remote" coho groups are likely to be consuming prey of similar size and trophic level, the PCB delivery mechanism (e.g., atmosphere vs runoff) apparently has more influence on the salmon PCB profile than biotransformation, suggesting that the wild chinook PCB profile is determined by feeding preference. Overall, wild salmon distributions primarily relate to trophic level, feeding preferences, and longevity, while metabolism appears at most a minor factor. The new classification protocol takes better advantage of individual congener PCB analyses and provides a better framework for understanding the PCB distributions in salmon and, potentially, the movement of individual PCB congeners through marine food chains than previous classification schemes.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".