Chlorinated Environmental Contaminants (Pcb, Ddt, Hch and Pcdd/Pcdf) from the Baltic Sea
Bibliographic record
Abstract
Baltic herring ( L.) is the most important fish species in the Baltic and for the Estonian fish processing industry. Consequently, the presence of toxicants in this species and in fish in general is of concern from the point of view of human health.The time and place of catch, i.e. the population location, play an important role when different regions are compared. Concentrations of chlorinated pesticides, polychlorinated biphenyls (PCBs), and polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDDFs) in Baltic Sea herring vary regionally. After the highest DDT and PCB concentrations in the herring muscle tissue off the German coast (Helsinki Commission (HELCOM) data), the most CDDF- contaminated fish are found off the eastern coast of Sweden in the Bothnian Sea.PCBs, DDT and metabolites, hexachlorobenzene (HCB) and hexachlorocyclohexane (HCH) isomers were measured in fish from Estonian coastal waters, since the middle 1970’s PCDFs since beginning of 2002. Aside from fish age, other characteristics – length, sex, weight, fat content, maturity, etc., - are to be taken into account in studies of the Persistent Organic Pollutants (POPs) in the Baltic fish organism.The amounts of toxicants obtained from fish in the mid 1970’s and in the mid of 1990’s do not represent human health risk, even when considering the maximum levels of organochlorines found in Baltic fish off the Estonian coast. The amounts are lower than the standards set by the World Health Organisation (WHO), even when the calculations are based on the consumption of 150 g of fish per day, as compared with the European average of 60 g per day.The results do not eliminate the need to monitor the toxicants in fish also in the future, because the use of hazardous chemicals in the Baltic Sea region will probably continue.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".