Modeling the fate of polychlorinated biphenyls in the inner Oslofjord, Norway
Bibliographic record
Abstract
A dynamic, segmented, multimedia fate and transport model has been developed, evaluated, and applied to gain insight regarding the behavior of seven polychlorinated biphenyl (PCB) congeners in the Inner Oslofjord (Norway). A comparison with a dated sediment core reveals that the model is not capable of reproducing some key features of the observed, historical, long-term trend in sediments, although better agreement is observed for six of seven PCB congeners over the last two decades. The model also underestimates the concentrations of PCBs in surface sediments in areas adjacent to the city of Oslo (Norway). In general, deviations between modeled and observed concentrations indicate that the historical emissions and discharges of PCBs are not sufficiently characterized and described. Net fluxes predicted by the model suggest that several congeners may have experienced a reversal of air-water and seawater-sediment exchange during the last decade or even earlier. The present study further suggests that the benefit of the proposed removal of the most contaminated sediments of the Inner Oslofjord needs to be assessed, with consideration of the relative contribution of current atmospheric inputs as well as the leaching of PCBs from less contaminated sediments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".