THE INDIUM-RICH SULFIDES AND RARE ARSENATES OF THE Sn-In-MINERALIZED MANGABEIRA A-TYPE GRANITE, CENTRAL BRAZIL
Bibliographic record
Abstract
Indium minerals and In-rich phases in Brazil are restricted to Paleo- to Mesoproterozoic tin-bearing within-plate magmatic zones in central Brazil. The most important concentration of indium is in the Mangabeira granitic massif, which is also the type locality of yanomamite (InAsO4·2H2O). The Sn–In-mineralized area of this massif is comprised of Li-rich siderophyllite granite, topaz–albite granite, quartz – Li-mica greisens and a vein of In-rich quartz–topaz rock, with up to 1 wt% In, mainly composed of quartz, topaz, zinnwaldite, arsenopyrite and cassiterite. Accessory minerals are sphalerite, ferberite, lollingite, chalcopyrite, bismuthinite, galena, stannite-group minerals, tennantite, argentite and roquesite. Secondary minerals comprise bornite, digenite, covellite, scorodite, phenakite, native copper, yanomamite, dzhalindite, metazeunerite and rare arsenates, like pharmacosiderite, segnitite, chenevixite, and goudeyite, and unknown Bi, Ba and Sn arsenates. Indium-rich stannite, as well as red In-rich and brown In-poor varieties of sphalerite, also are present. Zinc is replaced by indium, copper and iron in the sphalerite structure, probably according to the scheme Cu + In + Fe = 3Zn. Indium-rich sphalerite intergrown with roquesite, forming a texture interpreted as the product of roquesite exsolution, is documented here for the first time. The data obtained are consistent with the existence of the pseudoternary system stannite – sphalerite – roquesite and of a discontinuous solid-solution between yanomamite and scorodite.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".