Bhārata Strata · Maharashtra · Dharashiv · morphological twins
Places like cell 4880004060
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
0.92
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 4880003839
distance 0.081
#2 · Dharashivcell 4880004127
distance 0.093
#3 · Laturcell 4810001510
distance 0.098 · cross-district
#4 · Dharashivcell 4880003843
distance 0.101
#5 · Dharashivcell 4880003045
distance 0.104
#6 · Laturcell 4810001859
distance 0.104 · cross-district
#7 · Dharashivcell 4880003203
distance 0.106
#8 · Dharashivcell 4880003911
distance 0.11
#9 · Dharashivcell 4880003705
distance 0.11
#10 · Dharashivcell 4880003914
distance 0.113
#11 · Dharashivcell 4880002819
distance 0.115
#12 · Dharashivcell 4880001751
distance 0.123
#13 · Dharashivcell 4880003842
distance 0.124
#14 · Laturcell 4810000392
distance 0.124 · cross-district
#15 · Dharashivcell 4880003838
distance 0.126
#16 · Dharashivcell 4880003701
distance 0.127
#17 · Laturcell 4810000748
distance 0.128 · cross-district
#18 · Dharashivcell 4880001680
distance 0.129
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":4880004060}}}'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.