Bhārata Strata · Maharashtra · Bhandara · morphological twins
Places like cell 4710000795
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
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.262
lower = more alike (weighted)
The twins, closest first
#1 · Bhandaracell 4710000721
distance 0.262
#2 · Chandrapurcell 4730008407
distance 0.281 · cross-district
#3 · Bhandaracell 4710000548
distance 0.287
#4 · Bhandaracell 4710000549
distance 0.291
#5 · Bhandaracell 4710000551
distance 0.293
#6 · Bhandaracell 4710000588
distance 0.294
#7 · Bhandaracell 4710000714
distance 0.304
#8 · Gondiacell 4760000985
distance 0.306 · cross-district
#9 · Chandrapurcell 4730009606
distance 0.309 · cross-district
#10 · Bhandaracell 4710000761
distance 0.31
#11 · Bhandaracell 4710000372
distance 0.311
#12 · Bhandaracell 4710000583
distance 0.315
#13 · Bhandaracell 4710000545
distance 0.317
#14 · Chandrapurcell 4730009556
distance 0.32 · cross-district
#15 · Bhandaracell 4710000593
distance 0.322
#16 · Bhandaracell 4710000718
distance 0.323
#17 · Bhandaracell 4710000634
distance 0.324
#18 · Bhandaracell 4710000671
distance 0.326
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":4710000795}}}'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.