PCBs, PBDEs and pesticides released to the Arctic Ocean by the Russian Rivers Ob and Yenisei
Bibliographic record
Abstract
The Ob and Yenisei Rivers contribute 37% of riverine freshwater inputs to the Arctic Basin and thus represent an important pathway for the land-Arctic ocean exchange of contaminants. Sampling was carried out in the Yenisei (2003) and Ob (2005) River estuaries and Kara Sea to address the general lack of reliable dissolved contaminant flux data for these major rivers. Contaminant analyses were performed by high resolution mass spectrometry on sample extracts taken from filtered large volume water samples (50-100 L) and concentrated in situ onto XAD-2 resin columns. Hexachlorocyclohexanes (HCHs), the polychlorinated biphenyl (PCB) mixtures Sovol and trichlorodiphenyl, dichlorodiphenyltrichloroethane (DDT), as well as "penta" brominated technical mixtures of polybrominated diphenyl ethers (PBDEs) are important contributors to persistent organohalogen contamination for these waterways. Dissolved fluxes to the Kara Sea were estimated at sigmaHCH 246 kg/yr, sigmaPCB 63 kg/yr, sigmaDDT 16 kg/yr, hexachlorobenzene 8 kg/yr, alpha-endosulfan 8 kg/ yr, dieldrin 5 kg/yr, sigmaPBDE 4 kg/yr, and chlordanes 4 kg/yr. Contaminant fluxes from these rivers are similar to those reported for major Canadian rivers, confirming expectations that the Ob and Yenisei are also major point sources for the Arctic basin.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".