Open-water and under-ice seasonal variations in trace element content and physicochemical associations in fluvial bed sediment
Bibliographic record
Abstract
Across the circumpolar world, intensive anthropogenic activities in the southern reaches of many large, northward-flowing rivers can cause sediment contamination in the downstream depositional environment. The influence of ice cover on concentrations of inorganic contaminants in bed sediment (i.e., sediment quality) is unknown in these rivers, where winter is the dominant season. A geomorphic response unit approach was used to select hydraulically diverse sampling sites across a northern test-case system, the Slave River and delta (Northwest Territories, Canada). Surface sediment samples (top 1 cm) were collected from 6 predefined geomorphic response units (12 sites) to assess the relationships between bed sediment physicochemistry (particle size distribution and total organic carbon content) and trace element content (mercury and 18 other trace elements) during open-water conditions. A subset of sites was resampled under-ice to assess the influence of season on these relationships and on total trace element content. Concentrations of the majority of trace elements were strongly correlated with percent fines and proxies for grain size (aluminum and iron), with similar trace element grain size/grain size proxy relationships between seasons. However, finer materials were deposited under ice with associated increases in sediment total organic carbon content and the concentrations of most trace elements investigated. The geomorphic response unit approach was effective at identifying diverse hydrological environments for sampling prior to field operations. Our data demonstrate the need for under-ice sampling to confirm year-round consistency in trace element-geochemical relationships in fluvial systems and to define the upper extremes of these relationships. Whether contaminated or not, under-ice bed sediment can represent a "worst-case" scenario in terms of trace element concentrations and exposure for sediment-associated organisms in northern fluvial systems. Environ Toxicol Chem 2017;36:2916-2924. © 2017 SETAC.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".