Bhārata Strata · Maharashtra · Buldhana · morphological twins
Places like cell 4720003939
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 3 distinct districts
Index confidence
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.087
lower = more alike (weighted)
The twins, closest first
#1 · Buldhanacell 4720004091
distance 0.087
#2 · Buldhanacell 4720003907
distance 0.107
#3 · Buldhanacell 4720003905
distance 0.109
#4 · Jalnacell 4790006570
distance 0.119 · cross-district
#5 · Buldhanacell 4720003908
distance 0.122
#6 · Buldhanacell 4720003300
distance 0.122
#7 · Buldhanacell 4720003609
distance 0.123
#8 · Jalnacell 4790006583
distance 0.124 · cross-district
#9 · Akolacell 4670000293
distance 0.124 · cross-district
#10 · Buldhanacell 4720004767
distance 0.125
#11 · Buldhanacell 4720004910
distance 0.127
#12 · Buldhanacell 4720004170
distance 0.128
#13 · Buldhanacell 4720004193
distance 0.129
#14 · Buldhanacell 4720004168
distance 0.131
#15 · Jalnacell 4790006582
distance 0.132 · cross-district
#16 · Jalnacell 4790006629
distance 0.132 · cross-district
#17 · Buldhanacell 4720004477
distance 0.134
#18 · Buldhanacell 4720003832
distance 0.136
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":4720003939}}}'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.