Geophysical Investigation and Management Plan of a Shallow Landslide along the NH-44 in Atharamura Hill, Tripura, India
Bibliographic record
Abstract
In any effective landslide hazard mitigation plan, in-depth knowledge about the causes of instability is required. Consequently, it is essential to study geological, geotechnical, meteorological and anthropogenic factors that influence the landslide. For the present study a geophysical investigation has been carried out on a large landslide, on the slopes of Tertiary siltstones, mudstones, shales and sandstones at Atharamura Hill, Tripura. Different techniques have been used, including measurement of micro-slope using Total Station, clinometers and the LISCAD software for terrain modeling and determining the total volume of the material displaced and total area affected by landslides and analysis of soil properties to understand the present condition of the scarps. Results obtained through field investigation and laboratory testing revealed that the underlying cause of the slide could be (a) the adverse geological formation with unconsolidated sandy materials and occasional intersection of silt or clay layers, (b) the hydrological condition with continuous seepage through fractures, and (c) cutting of hill slopes for reconstructing and widening of the road (NH44). This latter anthropogenic influence has been triggered by an intense precipitation event during the monsoon season.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".