Trace Element Geochemistry and Mineral Inclusions Constraints on the Petrogenesis of a Marble–Hosted Ruby Deposit in Yunnan Province, China
Bibliographic record
Abstract
ABSTRACT Primary rubies in the Ailao Shan of Yunnan Province, China, are found in three layers of marble. However, the origin and source rocks of placer rubies in the Yuanjiang area remains unclear. Trace element geochemistry and inclusion mineralogy within these materials can provide information on their petrogenesis and original source. Zircon, rutile, mica group minerals, titanite, and apatite group minerals were the main solid inclusions identified within the placer Yuanjiang rubies, along with other mineral inclusions such as pyrite, pyrrhotite, plagioclase group minerals, and scapolite group minerals. Laser ablation inductively coupled plasma-mass spectrometry (LA-ICP-MS) measurements showed that the placer rubies are characterized by average values of Mg (31 ppmw), Ti (97 ppmw), V (77 ppmw), Cr (3326 ppmw), Fe (71 ppmw), and Ga (66ppmw). A trace-element oxide diagram, Fe values (<350 ppmw), and the mineral inclusion assemblage suggest marble sources for the placer ruby. Therefore, the Yuanjiang rubies (both primary and placer) are metamorphic, and this fits well with the observations that skarn and related minerals are mostly absent in this deposit. Yuanjiang rubies can be readily separated from the high-iron rubies of different geological types by their Fe content (<1000 ppmw). The discriminators Mg, Ga, Cr, V, Fe, and Ti have potential in separating Yuanjiang rubies from some other marble-hosted deposits, such as Snezhnoe. Nevertheless, geographic origin determination remains a challenge when considering the similarities in compositional features between the Yuanjiang rubies and rubies from some other marble-hosted deposits worldwide (e.g., Luc Yen). The presence of kaolinite group minerals and clusters of euhedral, prismatic zircon crystals in ruby suggest a Yuanjiang origin.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".