Bhārata Strata · Maharashtra · Nanded · morphological twins
Places like cell 4850006185
The MH-36 locality cells most similar to this Nanded 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 4 distinct districts
Index confidence
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.137
lower = more alike (weighted)
The twins, closest first
#1 · Nandedcell 4850006446
distance 0.137
#2 · Nandedcell 4850005091
distance 0.168
#3 · Nandedcell 4850007134
distance 0.225
#4 · Nandedcell 4850007344
distance 0.227
#5 · Yavatmalcell 5000000838
distance 0.238 · cross-district
#6 · Nandedcell 4850006361
distance 0.24
#7 · Nandedcell 4850005293
distance 0.244
#8 · Nandedcell 4850007916
distance 0.251
#9 · Hingolicell 4770000360
distance 0.253 · cross-district
#10 · Yavatmalcell 5000001504
distance 0.259 · cross-district
#11 · Nandedcell 4850006629
distance 0.265
#12 · Yavatmalcell 5000001160
distance 0.266 · cross-district
#13 · Nandedcell 4850005562
distance 0.268
#14 · Nandedcell 4850006756
distance 0.269
#15 · Washimcell 4990001657
distance 0.271 · cross-district
#16 · Nandedcell 4850008912
distance 0.272
#17 · Yavatmalcell 5000001458
distance 0.273 · cross-district
#18 · Nandedcell 4850008144
distance 0.274
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":485,"cluster_id":4850006185}}}'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.