Bhārata Strata · Maharashtra · Nanded · morphological twins
Places like cell 4850002486
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 3 distinct districts
Index confidence
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.13
lower = more alike (weighted)
The twins, closest first
#1 · Nandedcell 4850002134
distance 0.13
#2 · Beedcell 4700008640
distance 0.146 · cross-district
#3 · Nandedcell 4850004471
distance 0.149
#4 · Nandedcell 4850002150
distance 0.149
#5 · Nandedcell 4850004122
distance 0.153
#6 · Nandedcell 4850002578
distance 0.157
#7 · Nandedcell 4850002761
distance 0.163
#8 · Washimcell 4990002542
distance 0.163 · cross-district
#9 · Nandedcell 4850001897
distance 0.167
#10 · Beedcell 4700008454
distance 0.17 · cross-district
#11 · Nandedcell 4850002583
distance 0.173
#12 · Washimcell 4990001483
distance 0.176 · cross-district
#13 · Nandedcell 4850004128
distance 0.182
#14 · Beedcell 4700008458
distance 0.182 · cross-district
#15 · Nandedcell 4850006757
distance 0.184
#16 · Washimcell 4990001851
distance 0.185 · cross-district
#17 · Nandedcell 4850001196
distance 0.187
#18 · Washimcell 4990002026
distance 0.189 · 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":4850002486}}}'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.