Trace Element Content of Sedimentary Pyrite in Black Shales
Bibliographic record
Abstract
Laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) analyses of 1,407 sedimentary (diagenetic and syngenetic) pyrites from 45 carbonaceous shale and unconsolidated sulfidic sediment samples, ranging in age from Paleoarchean to present day, show a considerable range of trace element compositions. Arsenic, Ni, Pb, Cu, and Co are among the most abundant trace elements, with medians ranging from 100 to 1,000 ppm. Less abundant elements Mo, Sb, Zn, and Se have median ranges of 10 to 100 ppm, and Ag, Bi, Te, Cd, and Au have median ranges of 0.01 to 10 ppm. Our dataset reveals three main groups of trace elements that are incorporated into pyrite in different ways. Group 1 elements (As, Ni, Co, Sb, Se, and Mo) are contained uniformly throughout the pyrite and may be held within the pyrite crystal structure or as nanoinclusions evenly distributed within pyrite. Group 2 elements (Bi, Pb, Ag, Au, Te, and Cu) generally occur uniformly at low concentrations and may be incorporated into the pyrite structure but are highly variable at high concentrations, where they may also occur as microinclusions. Group 3 elements (Zn and Cd) tend to have highly variable abundances and generally occur in pyrite as microinclusions of sphalerite. Factor analyses of the dataset identified five factors that account for 65.4% of the variance in pyrite trace element concentrations. Factor 1 includes Pb, Bi, Au, and Te, and explains 18.1% of the variance, possibly due to As(II) (Qian et al., 2013) or As(III) substituting for Fe in pyrite, which induces the uptake of these elements. Factor 2 includes Co, Ni, and As and accounts for 13.6% of the variance, possibly due to the presence of As(I) substituting for S(II) in pyrite, which, in turn, promotes the uptake of Ni and Co. Factor 3 includes Zn and Cd and explains 12.3% of the variance and is due to the presence of sphalerite inclusions. Factor 4 includes Se, Ag, and Sb and explains 11.0% of the variance, which is believed to reflect coeval input of these elements into the oceans during periods of increased oxygenation. Factor 5 includes Mn, Cu, and Mo and explains 10.4% of the variance. It is likely that this behavior is due to these elements being delivered together to the sediments by adsorbing to Mn (hydro)oxides, which are released when the Mn (hydro)oxides dissolve in reducing bottom waters or pore waters. Variations in pyrite texture do not show consistent compositional patterns between different samples, though within the same sample later formed pyrite tends to have lower trace element abundance. Many trace elements associated with mafic extrusions/circulation of fluids through mafic rocks (Ni, Co) are more enriched in Archean sedimentary pyrite at times when mafic volcanism/circulation of fluids through mafic rocks was more active. Similarly, some trace elements tend to be more enriched in Phanerozoic pyrite due to increasing levels of atmospheric oxidation.
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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 | 0.002 | 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) | 0.001 | 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".