A Mass Balance Model Describing Multiyear Fate of Organochlorine Compounds in a High Arctic Lake
Bibliographic record
Abstract
Data collected over a 3-year study of a high arctic watershed and lake are used to understand the fate of organochlorine compounds (OCs) and form the basis of a mass balance contaminant fate model. The model uses the fugacity/aquivalence approach to describe OC dynamics between air, stream inflows and outflow, the water column, and surficial sediments. The steady-state model results indicate that stream inflows contributed from 96 to >99% of total chemical loadings, but 57-98% of total loadings were lost from the lake via the outlet, the percentage of which is controlled by the hydrologic regime of the high arctic lake. Conversely, only 0.4-3.4% of loadings were retained within the sediments due to the high export rate, minimal scavenging from the water column and low organic carbon fraction of the sediments. Using the unsteady-state model, which includes year-round processes, degradation was estimated to account for losses of 7-32% for the more persistent OCs and 42-50% for the less persistent OCs (alpha-HCH, gamma-HCH, and endosulfan I). If loadings were eliminated, water column concentrations would decline with half-lives <1 year for less persistent OCs and 1-2 years for the more persistent OCs, whereas the half-lives for OCs in sediment are 8-25 years.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".