Bhārata Strata · Maharashtra · Nashik · morphological twins
Places like cell 4870013128
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
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
43
morphology-v2 feature dimensions
Closest twin distance
0.128
lower = more alike (weighted)
The twins, closest first
#1 · Nashikcell 4870012986
distance 0.128
#2 · Nashikcell 4870013127
distance 0.159
#3 · Nashikcell 4870013131
distance 0.169
#4 · Nashikcell 4870012913
distance 0.169
#5 · Nashikcell 4870012915
distance 0.199
#6 · Nashikcell 4870013191
distance 0.203
#7 · Dhulecell 4740001739
distance 0.209 · cross-district
#8 · Dhulecell 4740002140
distance 0.216 · cross-district
#9 · Nashikcell 4870012469
distance 0.225
#10 · Dhulecell 4740001420
distance 0.226 · cross-district
#11 · Nashikcell 4870013126
distance 0.228
#12 · Dhulecell 4740001013
distance 0.234 · cross-district
#13 · Dhulecell 4740001753
distance 0.236 · cross-district
#14 · Nashikcell 4870012699
distance 0.236
#15 · Dhulecell 4740001737
distance 0.237 · cross-district
#16 · Nashikcell 4870013060
distance 0.24
#17 · Dhulecell 4740001207
distance 0.24 · cross-district
#18 · Nashikcell 4870013268
distance 0.241
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":4870013128}}}'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.