Bhārata Strata · Maharashtra · Parbhani · morphological twins
Places like cell 4890000140
The MH-36 locality cells most similar to this Parbhani 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 4 distinct districts
Index confidence
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.151
lower = more alike (weighted)
The twins, closest first
#1 · Parbhanicell 4890000326
distance 0.151
#2 · Parbhanicell 4890000133
distance 0.163
#3 · Parbhanicell 4890000058
distance 0.167
#4 · Parbhanicell 4890000450
distance 0.169
#5 · Parbhanicell 4890000318
distance 0.172
#6 · Parbhanicell 4890000549
distance 0.176
#7 · Parbhanicell 4890000219
distance 0.177
#8 · Beedcell 4700001502
distance 0.179 · cross-district
#9 · Parbhanicell 4890000193
distance 0.187
#10 · Parbhanicell 4890001123
distance 0.192
#11 · Parbhanicell 4890000304
distance 0.192
#12 · Nandedcell 4850002247
distance 0.193 · cross-district
#13 · Parbhanicell 4890000206
distance 0.193
#14 · Nandedcell 4850003249
distance 0.197 · cross-district
#15 · Nandedcell 4850002971
distance 0.198 · cross-district
#16 · Parbhanicell 4890000634
distance 0.198
#17 · Parbhanicell 4890001183
distance 0.199
#18 · Laturcell 4810005939
distance 0.199 · 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":489,"cluster_id":4890000140}}}'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.