A Review of Riverine Fluxes of Hexachlorocyclohexane and DDT to the Azov and Black Seas from the Former USSR and Russian Federation
Bibliographic record
Abstract
While the Azov and Black seas are subject to anthropogenic pollution to a much higher extent than any other seas, this has been little studied with only a few critical reviews of contaminant fluxes to these seas. Riverine fluxes of the organochlorine pesticides (OCPs) hexachlorocyclohexane (HCH) and DDT to the Azov and Black seas from the former Soviet Union and Russian Federation were thus reviewed for 1986 to 1996. The review was based on official data and data obtained by independent specialists. The amount of HCH used, and the intensity of usage, in these river catchments decreased during the review period. Concurrently, OCP concentrations in the rivers and their fluxes also decreased according to both official and independent data. A comparison of the official and the independent data sets for 1988 revealed significant differences, reflecting the need for more rigorous sampling and analytical protocols for both data sets. According to the OGSNK/GSN data, the flux rates of the five largest rivers were ranked (from largest to smallest) as follows: Don > Dnestr > Danube > Kuban > Dnepro (alpha-HCH); Danube > Don > Dnestr > Dnepro > Kuban (gamma-HCH); Dnestr > Danube > Don > Dnepro-Kuban (DDT+DDE). For rivers with lower annual riverine discharges, the DDT fluxes were surprisingly high (0.43 to 1.49 tonnes a(-1)). According to independent data for 1988 the rankings of the rivers was: Danube > Don > Dnepro > Dnestr > Kuban (alpha-HCH); Danube > Don > Dnestr > Dnepro > Kuban (gamma-HCH); Danube > Dnepro > Dnestr > Don > Kuban (DDT); Danube > Dnepro > Don > Kuban > Dnestr (DDE). The DDT flux estimates for small rivers derived from independent data were 19 to 46 times lower than those calculated using OGSNK/GSN data. According to the independent data, the total riverine OCP transport from the Russian Federation into the Azov Sea from 1988 to 1996 was 1.288 tonnes of gamma-HCH+alpha-HCH and 1.693 tonnes of DDT+DDE while for the Black Sea they were 3.830 tonnes and 5.116 tonnes for gamma-HCH+alpha-HCH and DDT+DDE, respectively.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".