Chiral Source Apportionment of Polychlorinated Biphenyls to the Hudson River Estuary Atmosphere and Food Web
Bibliographic record
Abstract
The New York/New Jersey Harbor Estuary is subject to significant contamination of polychlorinated biphenyls (PCBs) from numerous sources, including the historically contaminated Upper Hudson River, stormwater runoff and sewer overflows, and atmospheric deposition from PCBs originating from the surrounding urban area. However, the relative importance of these sources to the estuary's food web is not fully understood. Sources of PCBs to the estuary were apportioned using chiral signatures of PCBs in air, water, total suspended matter, phytoplankton, and sediment. PCBs 91, 95, 136, and 149 were racemic in the atmosphere of the estuary. However, the other phases contained nonracemic PCB 95 and to a lesser extent PCB 149. Thus, the predominant atmospheric source of these congeners is likely unweathered local pollution and not volatilization from the estuary. The similarity in chiral signatures in the other phases is consistent with dynamic contaminant exchange among them. Chiral signatures in the dissolved phase and total suspended matter were correlated with Upper Hudson discharge, suggesting thatthe delivery of nonracemic contaminated sediment from the Upper Hudson, not the atmosphere, controls phytoplankton uptake of some PCBs. Thus, measures to control PCB contamination in the Upper Hudson should be effective in reducing loadings to the estuary's aquatic ecosystem.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".