The Age and Source of Be and U Mineralization from the Baiyanghe Deposit
Bibliographic record
Abstract
Abstract Critical elements (e.g., Li, Be, U) are essential for energy, technology, and national defense applications. Therefore, it is important to develop effective exploration strategies, understand how these deposits form, and develop genetic models for these deposits. The Baiyanghe deposit, China, is the largest Be-U deposit in Asia. Despite several recent studies, the age and sources of mineralization remain controversial. Petrographic and geochemical analysis of host rocks indicate that the Yangzhuang rhyolite is underlain by an evolved alkali rhyolite tuff, rhyolitic to dacitic tuff, andesitic tuff, and basaltic tuff units. We used the Sm-Nd and Sr isotopic compositions of ore-bearing and barren fluorite and the U-Pb isotopic compositions of uranophane-beta to date the Be and U mineralization precisely. Our results indicate that two stages of Be mineralization occurred at 311 ± 12 and 261 ± 3 Ma. Whole rock geochemical data suggest the Yangzhuang rhyolite (YR) and the felsic tuff members of the underlying Tarbagatay Group are the sources of Be and U. The Sr and Nd isotope data suggest the first stage of Be mineralization formed from Yangzhuang rhyolite-derived fluids while mantle-derived fluids mobilized the second stage of Be mineralization. Our U-Pb geochronology indicates uranophane is associated with primary Be mineralization at 305.3 ± 1.3 Ma and reported uraninite mineralization at 246.1 ± 1.3 Ma due to supergene processes.
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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 | 0.000 | 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".