Bhārata Strata · Maharashtra · Nashik · morphological twins
Places like cell 4870009952
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
0.158
lower = more alike (weighted)
The twins, closest first
#1 · Nashikcell 4870009818
distance 0.158
#2 · Nashikcell 4870010348
distance 0.176
#3 · Nashikcell 4870011469
distance 0.184
#4 · Dhulecell 4740003187
distance 0.185 · cross-district
#5 · Dhulecell 4740000387
distance 0.19 · cross-district
#6 · Dhulecell 4740003008
distance 0.194 · cross-district
#7 · Dhulecell 4740000292
distance 0.196 · cross-district
#8 · Nashikcell 4870011683
distance 0.196
#9 · Nashikcell 4870009096
distance 0.198
#10 · Nashikcell 4870011231
distance 0.211
#11 · Nashikcell 4870011706
distance 0.211
#12 · Nashikcell 4870012055
distance 0.212
#13 · Dhulecell 4740000057
distance 0.216 · cross-district
#14 · Nashikcell 4870011575
distance 0.216
#15 · Nashikcell 4870010985
distance 0.216
#16 · Dhulecell 4740000381
distance 0.216 · cross-district
#17 · Dhulecell 4740000784
distance 0.218 · cross-district
#18 · Nashikcell 4870010344
distance 0.22
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":4870009952}}}'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.