Zr- AND Ba-RICH MINERALS FROM THE PONTE NOVA ALKALINE MAFIC-ULTRAMAFIC MASSIF, SOUTHEASTERN BRAZIL: INDICATION OF AN ENRICHED MANTLE SOURCE
Bibliographic record
Abstract
Zirconium- and Ba-rich minerals are found in gabbroic rocks from the Ponte Nova alkaline mafic-ultramafic massif in southeastern Brazil. The unusual mineralogical assemblage includes zirconolite, baddeleyite, Ba-rich alkali feldspar, and Ba- and Ti-rich biotite. Zirconolite of the Ponte Nova massif has higher levels of Zr (up to 1.172 apfu) than those registered in other terrestrial rocks and a prominent enrichment in the light rare-earth elements. Baddeleyite contains small quantities of Hf, Ti, and Fe. The Ba-rich alkali feldspar and Ba- and Ti-rich biotite contain up to 9.25 and 7.35 wt% BaO, respectively, and the biotite contains up to 12.01 wt% TiO(2). In the different intrusions of the Ponte Nova massif, such an unusual assemblage typifies the residual magma after the crystallization of clinopyroxene and olivine from previously enriched basanitic parental magma. The different trends of enrichments in REE and Th + U found for zirconolite of the intrusions of the Ponte Nova massif provide a better understanding of the variable degrees of enrichment of incompatible elements of the distinct gabbroic bodies. A lithospheric mantle source enriched in incompatible elements by the metasomatic action of volatile-rich fluids and with the presence of phlogopite or amphibole (or both) and other minor accessory phases could explain the presence of the Zr- and Ba-rich minerals in this gabbroic massif.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".