Bhārata Strata · Maharashtra · Bhandara · morphological twins
Places like cell 4710001255
The MH-36 locality cells most similar to this Bhandara cell across terrain, built form, land cover, climate dynamics and connectivity — ranked by a GUM-confidence-weighted (R24) distance, with the temporal block down-weighted. Each twin is a real cell with its own witnessed dossier.
Twins found
18
across 3 distinct districts
Index confidence
0.93
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.216
lower = more alike (weighted)
The twins, closest first
#1 · Nagpurcell 4840003049
distance 0.216 · cross-district
#2 · Bhandaracell 4710002115
distance 0.247
#3 · Bhandaracell 4710001253
distance 0.252
#4 · Nagpurcell 4840002115
distance 0.254 · cross-district
#5 · Bhandaracell 4710001849
distance 0.268
#6 · Bhandaracell 4710002099
distance 0.269
#7 · Nagpurcell 4840000919
distance 0.283 · cross-district
#8 · Bhandaracell 4710001742
distance 0.29
#9 · Bhandaracell 4710001100
distance 0.29
#10 · Bhandaracell 4710000349
distance 0.303
#11 · Bhandaracell 4710001982
distance 0.306
#12 · Bhandaracell 4710001501
distance 0.31
#13 · Nagpurcell 4840002209
distance 0.311 · cross-district
#14 · Bhandaracell 4710001687
distance 0.316
#15 · Gondiacell 4760003209
distance 0.32 · cross-district
#16 · Bhandaracell 4710001210
distance 0.33
#17 · Bhandaracell 4710001335
distance 0.331
#18 · Bhandaracell 4710001442
distance 0.332
witness: find_twins — morphology-twin-index-v2 (R24, GUM-confidence-weighted, magnitude-aware, temporal block down-weighted). Distance is the weighted feature distance; lower is more alike. Cross-district twins are the discriminative signal.
Re-witness these twins
curl -s https://api.gridrock.ai/mcp -H 'Content-Type: application/json' \
-H 'Accept: application/json, text/event-stream' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"find_twins",
"arguments":{"admin_code":471,"cluster_id":4710001255}}}'Scope: the live MH-36 cube. Twins are computed from the sha-verified morphology-v2 vector; the engine supplies no goodness/suitability ranking — only morphological similarity.