Bhārata Strata · Maharashtra · Nanded · morphological twins
Places like cell 4850000962
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
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.148
lower = more alike (weighted)
The twins, closest first
#1 · Nandedcell 4850002120
distance 0.148
#2 · Nandedcell 4850002656
distance 0.175
#3 · Nandedcell 4850001486
distance 0.205
#4 · Nandedcell 4850000241
distance 0.21
#5 · Beedcell 4700001190
distance 0.211 · cross-district
#6 · Beedcell 4700007909
distance 0.214 · cross-district
#7 · Nandedcell 4850001639
distance 0.217
#8 · Nandedcell 4850002212
distance 0.218
#9 · Nandedcell 4850000511
distance 0.218
#10 · Nandedcell 4850002192
distance 0.22
#11 · Beedcell 4700007994
distance 0.221 · cross-district
#12 · Nandedcell 4850002285
distance 0.222
#13 · Beedcell 4700001785
distance 0.222 · cross-district
#14 · Nandedcell 4850000154
distance 0.222
#15 · Nandedcell 4850001357
distance 0.223
#16 · Hingolicell 4770001597
distance 0.224 · cross-district
#17 · Washimcell 4990002721
distance 0.226 · cross-district
#18 · Washimcell 4990003228
distance 0.226 · cross-district
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":4850000962}}}'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.