Genetic relationships between skarn ore deposits and magmatic activity in the Ahar region, Western Alborz, NW Iran
Bibliographic record
Abstract
Abstract Paleocene to Oligocene tectonic processes in northwest Iran resulted in extensive I-type calc-alkaline and alkaline magmatic activity in the Ahar region. Numerous skarn deposits formed in the contact between Upper Cretaceous impure carbonate rocks and Oligocene-Miocene plutonic rocks. This study presents new field observations of skarns in the western Alborz range and is based on geochemistry of igneous rocks, mineralogy of the important skarn deposits, and electron microprobe analyses of skarn minerals. These data are used to interpret the metasomatism during sequential skarn formation and the geotectonic setting of the skarn ore deposit related igneous rocks. The skarns were classified into exoskarn, endoskarn and ore skarn. Andraditic garnet is the main skarn mineral; the pyroxene belongs to the diopside-hedenbergite series. The skarnification started with pluton emplacement and metamorphism of carbonate rocks followed by prograde metasomatism and the formation of anhydrous minerals like garnet and pyroxene. The next stage resulted in retro gradation of anhydrous minerals along with the formation of oxide minerals (magnetite and hematite) followed by the formation of hydrosilicate minerals like epidote, actinolite, chlorite, quartz, sericite and sulfide mineralization. In addition to Fe, Si and Mg, substantial amounts of Cu, along with volatile components such as H2S and CO2 were added to the skarn system. Skarn mineralogy and geochemistry of the igneous rocks indicate an island arc or subduction-related origin of the Fe-Cu skarn deposit.
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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 | 0.000 | 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) | 0.001 | 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".