Tourmaline trace element composition in volcanogenic massive sulfide Cu-Zn-Pb and clastic-dominated Zn-Pb deposits with applications to mineral exploration
Bibliographic record
Abstract
Tourmaline from thirteen volcanogenic massive sulfide (VMS) deposits, three clastic-dominated (CD) Zn Pb deposits, and four barren sediment-hosted tourmalinites were analyzed for major, minor, and trace elements to identify chemical criteria that distinguish tourmaline in VMS and CD deposits from other barren and mineralized environments. Tourmaline from VMS is mainly dravitic, with some deposits showing schorlitic and uvitic compositions, whereas CD Zn Pb and barren tourmalinite tourmaline spans the schorl-dravite transition and dravitic compositions, with few exceptions showing uvitic and foititic compositions. Tourmaline major element composition from VMS and CD is governed by heterovalent coupled substitutions, reflecting local processes specific to each deposit. In barren tourmalinites, the compositions are mainly controlled by the chemical composition of the host metasedimentary units. The VMS tourmaline shows higher Al, Mg, and V, whereas CD has higher Ca, Co, K, Mn, Li, La, Ce, Eu, Zn, and Pb; tourmalinites show higher Fe, Na, Ti, Sr, Cr, Sc, Sn, Ga, and Cu. A partial least-squares discriminant analysis (PLS-DA) model is used to classify VMS deposits, CD Zn Pb deposits, and barren tourmalinites. The results show that VMS tourmaline correlates with Mg, Sn, Ga, and V; CD Zn Pb tourmaline correlates with Pb, Zn, K, Mn, and Eu; and tourmaline from barren tourmalinites correlates with Fe, Ti, and Sr. These elements were used to build bivariate classification plots using element ratios that enhance the geochemical distinction of VMS and CD Zn Pb tourmaline from tourmaline in granite-related Sn W, orogenic gold, porphyry Cu-Mo-Au, iron oxide‑copper‑gold, and barren geological environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".