Bhārata Strata · Maharashtra · Buldhana · morphological twins
Places like cell 4720006348
The MH-36 locality cells most similar to this Buldhana 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 4 distinct districts
Index confidence
0.93
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.082
lower = more alike (weighted)
The twins, closest first
#1 · Buldhanacell 4720006425
distance 0.082
#2 · Buldhanacell 4720006691
distance 0.104
#3 · Akolacell 4670003565
distance 0.107 · cross-district
#4 · Buldhanacell 4720004351
distance 0.123
#5 · Buldhanacell 4720003891
distance 0.145
#6 · Buldhanacell 4720006594
distance 0.146
#7 · Buldhanacell 4720006143
distance 0.151
#8 · Buldhanacell 4720005450
distance 0.157
#9 · Akolacell 4670002262
distance 0.158 · cross-district
#10 · Jalgaoncell 4780006244
distance 0.161 · cross-district
#11 · Akolacell 4670003568
distance 0.162 · cross-district
#12 · Buldhanacell 4720003951
distance 0.165
#13 · Buldhanacell 4720006527
distance 0.166
#14 · Buldhanacell 4720005892
distance 0.166
#15 · Buldhanacell 4720003567
distance 0.167
#16 · Beedcell 4700004652
distance 0.167 · cross-district
#17 · Buldhanacell 4720006758
distance 0.168
#18 · Buldhanacell 4720003490
distance 0.17
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":472,"cluster_id":4720006348}}}'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.