Bhārata Strata · Maharashtra · Nashik · morphological twins
Places like cell 4870009546
The MH-36 locality cells most similar to this Nashik 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
43
morphology-v2 feature dimensions
Closest twin distance
0.109
lower = more alike (weighted)
The twins, closest first
#1 · Nashikcell 4870011933
distance 0.109
#2 · Nashikcell 4870009274
distance 0.132
#3 · Nashikcell 4870011471
distance 0.137
#4 · Nashikcell 4870009414
distance 0.141
#5 · Nashikcell 4870011594
distance 0.144
#6 · Dhulecell 4740000188
distance 0.145 · cross-district
#7 · Nashikcell 4870009275
distance 0.147
#8 · Nashikcell 4870008558
distance 0.15
#9 · Nashikcell 4870009549
distance 0.154
#10 · Nashikcell 4870012962
distance 0.156
#11 · Nashikcell 4870009821
distance 0.157
#12 · Dhulecell 4740000042
distance 0.157 · cross-district
#13 · Nashikcell 4870008557
distance 0.16
#14 · Dhulecell 4740000162
distance 0.162 · cross-district
#15 · Dhulecell 4740002433
distance 0.162 · cross-district
#16 · Dhulecell 4740000272
distance 0.163 · cross-district
#17 · Dhulecell 4740000410
distance 0.165 · cross-district
#18 · Dhulecell 4740000096
distance 0.165 · cross-district
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":487,"cluster_id":4870009546}}}'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.