Biogeochemical Cycling of Silver in Acidic, Weathering Environments
Bibliographic record
Abstract
Under acidic, weathering conditions, silver (Ag) is considered to be highly mobile and can be dispersed within near-surface environments. In this study, a range of regolith materials were sampled from three abandoned open pit mines located in the Iberian Pyrite Belt, Spain. Samples were analyzed for Ag mineralogy, content, and distribution using micro-analytical techniques and high-resolution electron microscopy. While Ag concentrations were variable within these materials, elevated Ag concentrations occurred in gossans. The detection of Ag within younger regolith materials, i.e., terrace iron formations and mine soils, indicated that Ag cycling was a continuous process. Microbial microfossils were observed within crevices of gossan and their presence highlights the preservation of mineralized cells and the potential for biogeochemical processes contributing to metal mobility in the rock record. An acidophilic, iron-oxidizing microbial consortium was enriched from terrace iron formations. When the microbial consortium was exposed to dissolved Ag, more than 90% of Ag precipitated out of solution as argentojarosite. In terms of biogeochemical Ag cycling, this demonstrates that Ag re-precipitation processes may occur rapidly in comparison to Ag dissolution processes. The kinetics of Ag mobility was estimated for each type of regolith material. Gossans represented 0.6–146.7 years of biogeochemical Ag cycling while terrace iron formation and mine soils represented 1.9–42.7 years and 0.7–1.6 years of Ag biogeochemical cycling, respectively. Biogeochemical processes were interpreted from the chemical and structural characterization of regolith material and demonstrated that Ag can be highly dispersed throughout an acidic, weathering environment.
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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 | 0.001 | 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".