Comparative Floc-Bed Sediment Trace Element Partitioning Across Variably Contaminated Aquatic Ecosystems
Bibliographic record
Abstract
Significantly higher concentrations of Ag, As, Cu, Ni and Co are found in floc compared to bed sediments across six variably impacted aquatic ecosystems. In contrast to the observed element and site-specific bed sediment trace element (TE) partitioning patterns, floc TE sequestration is consistently dominated by amorphous oxyhydroxides (FeOOH), which account for 30-79% of floc total TE concentrations, irrespective of system physico-chemistry or elements involved. FeOOH consistently occur in significantly higher concentrations in floc than within bed sediments. Further, comparative concentration factors indicate significantly higher TE reactivity of floc-FeOOH relative to sediment-FeOOH in all systems investigated, indicating that both the greater abundance and higher reactivity of floc-FeOOH contribute to enhanced floc TE uptake. Results indicate that floc-organics (live cells and exopolymeric substances, EPS) directly predict floc-FeOOH concentrations, suggesting an organic structural role in the collection/templating of FeOOH. This, in turn, facilitates the sequestration of TEs associated with floc-FeOOH formation, imparting the conserved FeOOH "signature" on floc TE geochemistry across sites. Results demonstrate that the organic rich nature of floc exerts an important control over TE geochemistry in aquatic environments, ultimately creating a distinct solid with differing controls over TE behavior than bed sediments in close proximity (<0.5 m).
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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 | 0.001 | 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) | 0.001 | 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".