Assessment of active tectonics of the Tripura-Mizoram fold belt (Surma Basin), North East India
Bibliographic record
Abstract
The Tripura-Mizoram fold belt is situated in the north-eastern part of India. Northeastern Himalaya including this region is tectonically very active, partly petroliferous, and has international attention from academicians and industry persons. This study aims at locating areas of recent tectonic vulnerability. Drainage networks are proxies of active faulting. Changes in geomorphic indices e.g., long profile analysis, basin-scale parameters, stream length gradient index and steepness index along the rivers in the eighteen watersheds extracted within the study area are evaluated. The Index of active tectonics (IAT) derived from the basin-scale parameters is classified into five classes: Class 1 (IAT =1.875–2.000), Class 2 (IAT = 2.001-2.375 ), Class 3 (IAT = 2.376-2.750), and Class 4 (IAT = 2.751-3.250) and Class 5 (IAT = 3.000‐3.320). Class 1 indicates the highest activity of tectonics. The tectonic sensitivity is also marked in micro-scale where rivers cross lineaments / faults. Elevations from source to mouth of individual consequent rivers of each watershed indicate the most vulnerable sections where the channels run along and across the faults or lineaments in watersheds 2, 14 and 15. The computed R 2 values and the IAT identify watershed 2 and watershed 15 as the tectonically most active. Well-bore stability issue from the Petroleum mining lease (PML) blocks needs to be taken care from watershed 2, 3 and 15. • Morphometric analysis performed in the hilly Tripura area. • Watersheds 2 and 15 are highly active tectonically. • Well-bore stability in these locations are to be taken care.
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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".