Investigating Landslides Induced by Hydrothermal Alteration Using Gravity and Magnetic Methods: A Case Study of Songgokerto, Indonesia
Bibliographic record
Abstract
Songgokerto, a Batu City, Indonesia subdistrict, features diverse topographical variations dominated by mountainous and valley landscapes.According to the 2024 data from the Regional Disaster Management Agency (BPBD) of Batu City, landslides frequently occur along Trunojoyo Road in Songgokerto.This road serves as a major transportation route connecting several key cities in East Java, including Batu City, Malang Regency, Kediri City, and Jombang Regency.Landslides in this region often lead to complete road closures, disrupting economic activities and raising safety concerns for travelers.The economic stagnation caused by blocked road access poses significant financial losses for the local government, as Batu City's revenue (PAD) primarily relies on agriculture and tourism, both of which depend on access through Trunojoyo Road.Geological methods provide valuable information about the distribution of rock formations locally.Geological mapping of the study area identified several rock units, including volcanic deposits, lava flows, Kawi-Buthak volcanic breccia, tuff deposits, and upper Quaternary volcanic breccia.Geophysical methods used in this study include gravity and magnetic surveys.The advanced method used is the minimum curvature inversion method.The gravity can detect faults using residual anomaly maps, with high values ranging from 0.1 to 3.0 mGal, moderate values from -0.8 to -0.09 mGal, and low values from -3.9 to -0.9 mGal.Meanwhile, the magnetic method provides insights into hydrothermal alteration by analyzing residual magnetic anomaly maps, ranging from -387.1 nT to 401.9 nT.Integrating geological and geophysical methods can establish a correlation between hydrothermal alteration zones and landslide activity.The correlation results between gravity, magnetic, and geological methods reached 99.4%, hydrothermal alteration zones and landslide activity had a correlation of up to 99.8%.The results indicate that both methods validate each other, yielding an accurate alteration map.Further correlation of this alteration map with landslide occurrences supports the hypothesis that hydrothermal alteration contributes to the landslides in the study area.Periodic reviews every year to obtain periodic data and references for government mitigation plans.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".