PARAGENETIC ASSEMBLAGES OF BERYLLIUM SILICATES AND PHOSPHATES FROM THE NANPING No. 31 GRANITIC PEGMATITE DYKE, FUJIAN PROVINCE, SOUTHEASTERN CHINA
Bibliographic record
Abstract
Silicates and phosphates are two principal groups of the more than 100 beryllium minerals, but they are rarely documented to cocrystallize as magmatic phases. Here, we describe complex paragenetic assemblages of various species of Be minerals in five zones from the outer contact inward in the Nanping No. 31 pegmatite dyke, in southern China. Three types of magmatic paragenetic assemblages of Be minerals are distinguished. The first type consists primarily of Be silicates (beryl + phenakite) in the outer zones (zones I–II), which likely results from Al-poor melts. The second type is typically represented by the complex association of Be phosphates + silicates, typically interstitial to saccharoidal albite in zone II. This type shows a general sequence: phenakite → hydroxylherderite or hurlbutite → fluorapatite → beryl, which is suggestive of the competitive predominance of phosphorus over silicon during the crystallization of Be minerals. The third is uniquely described by Cs-rich beryl in zones III and IV. This type of beryl is easily altered by hydrothermal fluids, leading to secondary Cs-poor beryl and nanpingite. Our results indicate that crystallization and the sequential assemblages of Be minerals are clearly related to the environment and evolution of pegmatite crystallization.
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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 | 0.000 |
| 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 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".