Bhārata Strata · Maharashtra · Parbhani · morphological twins
Places like cell 4890000409
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 3 distinct districts
Index confidence
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.091
lower = more alike (weighted)
The twins, closest first
#1 · Parbhanicell 4890000339
distance 0.091
#2 · Parbhanicell 4890000374
distance 0.091
#3 · Parbhanicell 4890000446
distance 0.099
#4 · Parbhanicell 4890000412
distance 0.109
#5 · Parbhanicell 4890000293
distance 0.117
#6 · Parbhanicell 4890000491
distance 0.118
#7 · Laturcell 4810005943
distance 0.128 · cross-district
#8 · Parbhanicell 4890000328
distance 0.13
#9 · Parbhanicell 4890000447
distance 0.132
#10 · Laturcell 4810005974
distance 0.136 · cross-district
#11 · Nandedcell 4850003340
distance 0.136 · cross-district
#12 · Laturcell 4810006072
distance 0.136 · cross-district
#13 · Parbhanicell 4890000309
distance 0.139
#14 · Parbhanicell 4890000345
distance 0.142
#15 · Nandedcell 4850003424
distance 0.143 · cross-district
#16 · Parbhanicell 4890000406
distance 0.143
#17 · Parbhanicell 4890000463
distance 0.144
#18 · Parbhanicell 4890000490
distance 0.145
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":4890000409}}}'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.