PCBs Transfer in Marine Trophic Webs: From Fish to Top Predators
Bibliographic record
Abstract
Coastal expansion, industry, crude sewages, intensive agriculture and oil spills, have a high impact on the marine environment worldwide. Although the release of persistent organic pollutants (POPs) into marine ecosystems has prompted diverse conservation measures, there is still a lack of research studies and legal under-regulation on this topic. The polychlorinated biphenyls (PCBs) are a family of 209 hydrophobic chlorinated compounds characterized by high persistence, bioaccumulative potential and toxic properties, reflecting the lipophilicity and widespread distribution of these compounds in the environment. Once in the marine environment, they enter the trophic web and tend to accumulate and biomagnify in organisms, rapidly reaching the long-lived apex predators. In this sense, a global decreasing trend has been observed in the regions where PCBs pollution was initially high –which usually correspond to areas close to point sources of organochlorine compound release -Lake Ontario, Baltic Sea, Waden Sea, North Sea, etc.; however, an accumulating tendency has been observed in regions located far from these sources as a probable consequence of atmospheric transport, redistribution and new sources. Therefore, by means of literature review and analysis, this chapter will deal with the hypothesis by which the Northern Hemisphere marine tropic webs are increasingly accumulating PCBs vs. the Southern Hemisphere’s. Further, the South has recently emerged as a concern in terms of pollution, as these water masses are likely to become a major sink for the most persistent forms of organochlorines in the following years. Beyond this, this chapter address PCB origins, uptake dinamics, biotransformation, bioaccumulation and documented impacts over these marine animals, approaching a‘state of knowledge’ and setting an integrated basis for future tiered studies to estimate the actual human exposure risk through seafood consumption and giving support for future conservational measures.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".