Bhārata Strata · Maharashtra · Dharashiv · morphological twins
Places like cell 4880001216
The MH-36 locality cells most similar to this Dharashiv 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 2 distinct districts
Index confidence
0.93
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.081
lower = more alike (weighted)
The twins, closest first
#1 · Dharashivcell 4880001556
distance 0.081
#2 · Dharashivcell 4880002151
distance 0.114
#3 · Dharashivcell 4880001652
distance 0.114
#4 · Dharashivcell 4880002511
distance 0.117
#5 · Dharashivcell 4880002004
distance 0.118
#6 · Dharashivcell 4880001391
distance 0.131
#7 · Dharashivcell 4880002387
distance 0.131
#8 · Laturcell 4810000737
distance 0.133 · cross-district
#9 · Dharashivcell 4880002167
distance 0.135
#10 · Dharashivcell 4880001730
distance 0.135
#11 · Dharashivcell 4880002442
distance 0.136
#12 · Laturcell 4810000948
distance 0.14 · cross-district
#13 · Dharashivcell 4880001653
distance 0.14
#14 · Dharashivcell 4880001567
distance 0.142
#15 · Dharashivcell 4880001491
distance 0.148
#16 · Laturcell 4810001154
distance 0.154 · cross-district
#17 · Laturcell 4810001325
distance 0.154 · cross-district
#18 · Dharashivcell 4880002444
distance 0.157
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":488,"cluster_id":4880001216}}}'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.