Bhārata Strata · Maharashtra · Washim · morphological twins
Places like cell 4990000008
The MH-36 locality cells most similar to this Washim 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
0.089
lower = more alike (weighted)
The twins, closest first
#1 · Washimcell 4990000076
distance 0.089
#2 · Washimcell 4990000072
distance 0.101
#3 · Buldhanacell 4720000076
distance 0.116 · cross-district
#4 · Washimcell 4990000062
distance 0.118
#5 · Washimcell 4990000011
distance 0.124
#6 · Washimcell 4990000020
distance 0.127
#7 · Buldhanacell 4720000119
distance 0.127 · cross-district
#8 · Washimcell 4990000027
distance 0.14
#9 · Akolacell 4670000124
distance 0.142 · cross-district
#10 · Washimcell 4990000159
distance 0.146
#11 · Washimcell 4990000060
distance 0.151
#12 · Washimcell 4990000095
distance 0.151
#13 · Washimcell 4990000019
distance 0.154
#14 · Buldhanacell 4720005268
distance 0.154 · cross-district
#15 · Buldhanacell 4720005237
distance 0.155 · cross-district
#16 · Washimcell 4990000096
distance 0.157
#17 · Buldhanacell 4720000116
distance 0.157 · cross-district
#18 · Washimcell 4990000732
distance 0.159
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":499,"cluster_id":4990000008}}}'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.