Halogen signatures of biotites from the Maher-Abad porphyry copper deposit, Iran: characterization of volatiles in syn- to post-magmatic hydrothermal fluids
Bibliographic record
Abstract
Abstract Copper and gold mineralization in the Maher-Abad area, eastern Iran, is closely related to multiple episodes of emplacement of a late Eocene granodiorite into a quartz-monzonitic stock and andesitic volcaniclastic rocks. Hypogene and supergene porphyry Cu–Au mineralization occurred within the porphyritic granodiorite and quartz-monzonite host rocks extensively altered into dominantly potassic, propylitic, phyllic, and argillic assemblages. Temperature and pressure estimates using the plagioclase–hornblende thermometer and Al-in-hornblende barometer indicate that the granodiorite intruded at 758 ± 10°C and 1.4 ± 0.2 kbar. Biotites from the alteration zones have more variable AlIV than those in the fresh granodiorite, but nearly all are close to the ideal phlogopite composition. Biotite compositions display an increase in Al2O3, FeO, TiO2, and Cl, but a decrease in SiO2 and F, from the porphyritic granodiorite and potassic to the transitional phyllic alteration zones. Biotite from the potassic zone (X phl = 0.63–0.67) possesses a moderate F content (0.53 to 0.82 wt.%) that is significantly higher than that in the phyllic zone (0.22 to 0.38 wt.%), exhibiting a positive correlation with X Mg and negative correlation with Cl. With a decrease in the temperature, log (fH2O/fHF) and log (fH2O/fHCl) values calculated for fluids equilibrated with biotite increase progressively from the granodiorite through the potassic to the phyllic zones, whereas log (fHF/fHCl) shifts towards more negative values. Fugacity ratio trends in the Maher-Abad porphyry copper deposit are quite similar to those of other porphyry copper systems. The decrease in halogen content of hydrothermal fluids towards outer parts of the deposits reflects an increase in the degree of mixing between magmatic fluid and meteoric water. Keywords: biotitehalogen fugacityhydrothermal alterationCu–Au porphyryMaher-AbadIran Acknowledgements This contribution is a part of the first author's PhD thesis with laboratory studies carried out at the Institute of Mineralogy and Economic Geology, RWTH Aachen University, Germany. Funding for this project was provided by the Ministry of Science, Research and Technology, Iran. My grateful appreciation is extended to Professor F. M. Meyer for all his constructive scientific criticisms and R. Klinghardt for his assistance in electron microprobe analysis. Deserved thanks go to B. Ahin for his field assistance.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.013 | 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".