Numerical Simulation of the Self‐Organizational Origin of Concentrically Zoned Aggregates of Siderite and Pyrite in Sediment‐Hosted Massive Sulfide Deposits
Bibliographic record
Abstract
Abstract Concentrically zoned pyrite aggregates (CZPA) are common in sediment‐hosted massive sulfide (SHMS) deposits and have been widely used to interpret the ore‐forming processes. There is considerable uncertainty, however, over the formation of aggregates that are oscillatorily zoned and contain randomly‐orientated pyrite microcrystals. Guided by the results of examination of the micro‐textures of CZPA and in‐situ chemical analyses, we conducted a quantitative diffusion‐reaction simulation to assess the mechanism of CZPA formation. Our study shows that oscillatory zoning results from the feedback between the diffusion of reactants and the nucleation‐growth of Fe‐sulfides. Externally derived Fe 2+ diffuses into the early diagenetic sediments containing decomposing organic matter (2CH 2 O + SO 4 2− = 2HCO 3 − + H 2 S) and reacts with H 2 S to form a pyrite layer via an intermediate pathway (Fe 2+ + H 2 S → FeS + 2H + , FeS + H 2 S → FeS 2 + H 2 ). This growth of pyrite layers depletes the local concentration of reactants and suppresses nucleation until the diffusive reaction front advances and another layer is formed. Intermediate phases, for example, mackinawite, nucleate instead of pyrite, because of their greater ease of nucleation due to the low surface tension, and lead to the domination of nucleation over growth. The nucleation of mackinawite and occurrence of siderite in the CZPA are consistent with a low temperature, high pH, anoxic early diagenetic environment. Our study demonstrates that CZPA in SHMS deposits are formed by intrinsic self‐organizational processes rather than by extrinsic changes of ore‐forming fluids. The CZPA in SHMS deposits are thus indicative of their diagenetic origin with Fe 2+ infiltrated and diffused from hydrothermal fluids into the sediments.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".