Transformation of Fe-bearing minerals from Dongsheng sandstone-type uranium deposit, Ordos Basin, north-central China: Implications for ore genesis
Bibliographic record
Abstract
Abstract Iron-bearing mineral assemblages and their distribution patterns directly reflect the redox environment in sediments, which plays a decisive role in the migration and precipitation of U. The Dongsheng sandstone-type U deposit hosted in fluvial and/or deltaic sandstones of the lower member of the Middle Jurassic Zhiluo Formation in the northeastern Ordos Basin has experienced multiple fluid events that impacted the redox conditions. Highly enriched in barren gray sandstones, pre-ore U (Umean = 12.05 ppm) associated with Fe-Ti oxides, clay minerals, and organic matter is likely one of the key sources of U for the mineralization. Different contents of Fe-bearing minerals, including biotite, Fe-Ti oxides, pyrite, hematite, goethite, and chlorite that were formed or altered under different redox conditions, resulted in sandstone units with distinct colors. The red sandstone is hematite-rich, indicating a highly oxidizing environment. The green sandstone is chlorite-rich and formed because of reducing hydrocarbon-rich fluids that overprinted the hematite-rich sandstone. The barren and mineralized gray sandstones consist of pyrite (with a higher content in mineralized sandstones), Fe-Ti oxides, and carbonaceous debris, which are indicators of a reducing environment. Based on the paragenetic relationship and sulfur isotopic compositions of ore-stage pyrite, bacterial sulfate reduction was responsible for the formation of framboidal pyrite (δ34S = –31.2 to –3.8‰), and the sulfur of this pyrite mainly came from the oxidation of pre-ore pyrite (δ34S = –19.1 to +20.3‰). Euhedral and cement pyrite overprinting framboids were produced via Ostwald ripening with δ34S values ranging from –56.9 to –34.3‰, lower than any values of framboidal pyrite. Therefore, these mineralogical and geochemical characteristics of the Dongsheng deposit suggest U mineralization involves both biogenic and abiogenic redox processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".