Petrologic exploration criteria for magmatism-related uranium deposits: a review
Bibliographic record
Abstract
Magmatic rocks host different types of uranium deposits that can range from magmatic/high-temperature hydrothermal systems to post-magmatic, low-temperature hydrothermal deposits. The uranium mineralization in the syn- or late-magmatic systems could be divided into three types. (1) Magmatic deposits related to differentiated peralkaline complexes that are typically rich in SiO2 (>72 wt%) and poor in (B: Fe+Mg+Ti)<100 (in cation values). The Na/K ratio in these rocks is > 1 and they have high contents of incompatible lithophile elements such as Nb, Ta, Zr, REE, Th and U. (2) Magmatic deposits related to strongly peraluminous magmas, derived from partial melting of crust. They are the result of a low degree partial melting of crustal arkosic (quartz-feldspathic) rocks with high SiO2 (>74 wt%), low B < 40 and positive values for (A: Al-[Na+K + 2Ca]) (in cation values)), and are mostly accompanied by Li and F minerals. (3) Magmatic deposits related to the evolved hot peralkaline or metaluminous (A [A2] - to I- types) magma that assimilated fertile materials of the crust and endured a high rate of crystal fractionation. They mostly form high-temperature (vein-type and hybrid system) deposits. The rate of fluid in magma is important for the formation of this type of deposit. Therefore, the fertile magmas for this type of deposits typically have SiO2 >72 wt%, positive values of A, B < 50 and K/Rb < 150. They are possibly rich in Mo and F. Dry-hot alkaline felsic volcanic rocks are more suitable for post-magmatic low-temperature hydrothermal deposits. The altered intrusive rocks with about 200 Ma age and higher contents of refractory minerals, are suitable candidates for supporting the post-magmatic, low-temperature hydrothermal uranium mineralization.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".