Bhārata Strata · Maharashtra · Nashik · morphological twins
Places like cell 4870012951
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
0.16
lower = more alike (weighted)
The twins, closest first
#1 · Nashikcell 4870012879
distance 0.16
#2 · Nashikcell 4870011937
distance 0.165
#3 · Dhulecell 4740000098
distance 0.166 · cross-district
#4 · Nashikcell 4870011820
distance 0.168
#5 · Nashikcell 4870011920
distance 0.178
#6 · Nashikcell 4870011593
distance 0.179
#7 · Nashikcell 4870012878
distance 0.185
#8 · Dhulecell 4740000143
distance 0.186 · cross-district
#9 · Nashikcell 4870008398
distance 0.195
#10 · Nashikcell 4870012038
distance 0.199
#11 · Dhulecell 4740003179
distance 0.204 · cross-district
#12 · Dhulecell 4740002913
distance 0.209 · cross-district
#13 · Nashikcell 4870012815
distance 0.212
#14 · Dhulecell 4740000233
distance 0.215 · cross-district
#15 · Nashikcell 4870012059
distance 0.215
#16 · Dhulecell 4740002300
distance 0.215 · cross-district
#17 · Nashikcell 4870012736
distance 0.219
#18 · Dhulecell 4740000124
distance 0.221 · 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":4870012951}}}'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.