Geological Characterization of Rare Earth Elements in Aceh’s Igneous Rocks: A Step Toward Sustainable Mining
Bibliographic record
Abstract
This study investigates and characterizes the presence of rare earth elements (REEs) in igneous rock samples from the Lokop geological complex in East Aceh, Indonesia.The Lokop geological area is strategically significant due to its underexplored potential for REE resources, since Indonesia aims to enhance its contribution to the global low-carbon transition through sustainable mineral development.Twenty rock and soil samples were analyzed using X-ray diffraction (XRD) and scanning electron microscopy (SEM-EDS) for mineralogical and petrographic characterization, revealing albite-rich plagioclase feldspars hosted in quartzite.REE trace analysis via inductively coupled plasma optical emission spectrometry (ICP-OES) showed Total Rare Earth Elements and Yttrium (TREE+Y) concentrations ranging from 111.20 to 1727.30ppm.The content of Light Rare Earth Elements (LREEs), ranging from 75.30 to 1225.40 ppm, was significantly higher than that of Heavy Rare Earth Elements (HREEs), which ranged from 35.90 to 501.90 ppm.The highest TREE+Y concentration (1727.30ppm) was observed in an andesitic rock sample from the Kolon riverbank outcrop, predominantly composed of LREEs, including Cerium (944.90 ppm) and Neodymium (195.50 ppm).The LREE concentration, primarily Lanthanum (498.70 ppm), was also present in this sample.This research provides an important foundation for the sustainable development of Indonesian REE resources, contributing to the global low-carbon economy.
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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 | 0.001 | 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".