www.scielo.br/aabc Chemical composition of gahnite and degree of pegmatitic fractionation in the Borborema Pegmatitic Province, northeastern Brazil
Bibliographic record
Abstract
presented by VALDEREZ FERREIRA Gahnite electron probe microanalyses from three pegmatites (Mirador, Capoeira and Quintos) of the Borborema Peg-matitic Province in northeastern Brazil allowed to determine molar compositions ranging from 86.22 to 95.41 mol% gahnite (ZnAl2O4), 1.51 to 6.62 mol % hercynite (Fe2+Al2O4), 0.11 to 5.89 mol % spinel (MgAl2O4), 1.48 to 2.74 mol % galaxite (MnAl2O4), and Zn/FeTotal atomic ratios ranging from 11.53 to 60.87. These data compared with gah-nite compositions from albite subtype pegmatites from Cap de Creus, Spain (Zn/FeTotal between 10 and 60) and from the source granite of the Separation Rapids pegmatite field, Ontario, Canada (Zn/FeTotal =3.5) indicate a high degree of fractionation of the studied pegmatites. This interpretation agrees with conclusions based on compositional data of tourmaline (vacancy in X-site 0.42 to 0.49), white mica (K/Rb between 8 and 33), feldspar (K/Rb between 8 and 109), garnet (Mn/(Mn+Fe2+) between 0.93 and 0.97) and in Nb-Ta oxides (Mn/(Mn+Fe2+)>0.5) in the same pegmatites. Key words: gahnite, rare-element granitic pegmatites, Borborema Pegmatitic Province, mineral chemistry.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".