Fluid Inclusions and REE Geochemistry of White and Purple Fluorite: Implications for Physico-Chemical Conditions of Mineralization; an Example from the Pinavand F Deposit, Central Iran
Bibliographic record
Abstract
The Pinavand fluorite deposit is hosted by lower Cretaceous carbonate rocks in the structural-geological transitional zone of Central Iran. The purple and white fluorite occur, respectively, as early replacement masses and late cross-cutting veins. Both fluorites have different and distinct physicochemical characteristics. The purple fluorite has higher homogenization temperatures of fluid inclusions (170–260 °C) and lower ∑REE (1.6 ppm) and Y (1.3 ppm) than the white variety (90–150 °C, 11.12 ppm, and 21.3 ppm, respectively). All fluorite samples show positive Y anomalies (Y/Y*) in the range of 1.15–3.5. The average values of La/Ho in the purple and white fluorites are 23.1 and 3.4, respectively. The purple fluorite samples have lower Y/Ho values (an average of 63.45) than the white fluorite samples (an average of 87.64). The Tb/Ca ratio in the Pinavand fluorites ranges between 0.0000000348 and 0.00000105, and the Tb/La ratio varies between 0.01 and 0.4; these values suggest that both fluorite types are “hydrothermal” in origin. The purple fluorites have a lower Sr and a negative Eu anomaly. These differences in concentrations and ratios of various REE suggest that the physico–chemical conditions of mineralization changed during fluorite deposition at the Pinavand. These changes correspond to an increase in oxygen fugacity and pH, which occurred during white fluorite mineralization at lower temperatures. The δ34S values of the Pinavand barite samples (an average of 23.25‰) are similar to those of seawater sulfate in the upper Proterozoic. The δ34S values of galena range from −0.2‰ to −3.7‰, compatible with bacterial sulfate reduction (BSR). These features are similar to those in the hydrothermal and magmatic deposits.
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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 | 0.002 | 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) | 0.000 | 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 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".