ANALISIS SPASIAL ZONA POTENSI RAWAN LONGSOR DISEKITAR RUAS JALAN RAYA MATARAM-TANJUNG
Bibliographic record
Abstract
This research aims to analyze the spatial distribution of landslide prone zones around Mataram-Tanjung highway. The second objective is to determine whether the utilization of GIS can be used properly to analyze the potential prone to landslides in an area based on several indicators used. The method used is overlay analysis and utilizing Geographic Information System (GIS) application. The variables used are soil type, rainfall, slope, geological type and land cover type. The result of the analysis shows that the distribution of landslide prone potential zone in the study area has 4 classes, namely very low landslide prone potential class, low prone potential, medium prone potential and high prone potential. The application of sapsial analysis by utilizing GIS can help in predicting an area that is potentially prone to landslides, this is reinforced by the results of field validation where the results of the analysis have been appropriate to describe the existing conditions.
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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 | 0.004 | 0.004 |
| 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) | 0.004 | 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".