Bhārata Strata · Maharashtra · Nanded · morphological twins
Places like cell 4850000108
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
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
44
morphology-v2 feature dimensions
Closest twin distance
0.061
lower = more alike (weighted)
The twins, closest first
#1 · Nandedcell 4850000090
distance 0.061
#2 · Nandedcell 4850000013
distance 0.081
#3 · Nandedcell 4850000072
distance 0.093
#4 · Nandedcell 4850000063
distance 0.093
#5 · Nandedcell 4850000022
distance 0.095
#6 · Nandedcell 4850000025
distance 0.102
#7 · Nandedcell 4850000001
distance 0.107
#8 · Nandedcell 4850000012
distance 0.11
#9 · Nandedcell 4850000043
distance 0.117
#10 · Nandedcell 4850000008
distance 0.119
#11 · Akolacell 4670000769
distance 0.124 · cross-district
#12 · Washimcell 4990003513
distance 0.125 · cross-district
#13 · Akolacell 4670000452
distance 0.128 · cross-district
#14 · Akolacell 4670000832
distance 0.13 · cross-district
#15 · Akolacell 4670000836
distance 0.13 · cross-district
#16 · Nandedcell 4850000103
distance 0.132
#17 · Akolacell 4670001853
distance 0.132 · cross-district
#18 · Akolacell 4670001185
distance 0.133 · 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":4850000108}}}'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.