THE ARSHAN REE CARBONATITES, SOUTHWESTERN TRANSBAIKALIA, RUSSIA: MINERALOGY, PARAGENESIS AND EVOLUTION
Bibliographic record
Abstract
The Arshan carbonatites in the Transbaikalia region of Siberia consist of sovite with high concentrations of the REE, Sr, Ba, and SO 3 , and low concentrations of Nb and P 2 O 5 . There was a high fugacity of oxygen and fluid activity at the time of formation of these carbonatites, and they were later altered by hydrothermal solutions. Bastnasite formed as a magmatic mineral in the carbonatites, on the basis of petrographic evidence and fluid-inclusion data. The recrystallization of calcite, the replacement of bastnasite and phlogopite, and the formation of secondary sulfates, strontianite, calcite and fluorite resulted from a hydrothermal process. The 87 Sr/ 86 Sr values of minerals in the Arshan carbonatites are higher than in many other carbonatites, but are similar to those in the continental basalts of Transbaikalia. The δ 34 S CDT values resemble those of other Transbaikalia carbonatites and alkaline rocks. The δ 13 C V–PDB isotopic values in the carbonatite plot within the field defined for primary igneous carbonatites. On the other hand, δ 18 O V–SMOW values for the Arshan bastnasite is only partially within the usual range of mantle values. The altered carbonatites are characterized by lighter δ 18 O values, probably because of the influence of meteoric water. The carbonatites were formed from an enriched source in the mantle and crystallized rapidly at shallow depth.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".