Non-Steady State Modeling of Arsenic Diagenesis in Lake Sediments
Bibliographic record
Abstract
A one-dimensional reactive transport model describing the coupled biogeochemical cycling of As, C, O, Fe, and S was used to interpret an extensive geochemical sediment (As, Fe, S, (210)Pb, (137)Cs, C(org)) and pore water (As, Fe, SO(4)(2-), SigmaS(-II) and pH) data set collected in the perennially oxygenated basin of an oligotrophic lake. Historical variations in atmospheric deposition of As and SO(4)(2-) were explicitly included as upper boundary conditions in the model calculations. The results show that the depth profile of sediment-bound As reflects both the past changes in As deposition and the diagenetic redistribution of As among the Fe(III) oxyhydroxide and Fe(II) sulfide pools. The model-predicted benthic release of dissolved As to the water column peaks 26 years after the maximum anthropogenic As input to the lake, which occurred around 1950. Two major environmental forcings of the benthic recycling of As are the organic matter degradation in the sediment and the atmospheric sulfate deposition to the lake. More oxidizing conditions associated with lower organic matter degradation rates yield a greater abundance of Fe(III) oxyhydroxides in the topmost sediment, which act as a barrier to pore water As. Variations in sulfate availability have more complex effects on benthic As remobilization, since sulfide produced by sulfate reduction may enhance both the uptake of dissolved As through the precipitation of Fe(II) sulfides and the release of dissolved As through the reductive dissolution of Fe(III) oxyhydroxides.
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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 | 0.001 |
| 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) | 0.002 | 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".