Bhārata Strata · Maharashtra · Parbhani · morphological twins
Places like cell 4890003749
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
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.097
lower = more alike (weighted)
The twins, closest first
#1 · Parbhanicell 4890003691
distance 0.097
#2 · Parbhanicell 4890004118
distance 0.148
#3 · Parbhanicell 4890002497
distance 0.171
#4 · Jalnacell 4790001810
distance 0.185 · cross-district
#5 · Parbhanicell 4890003655
distance 0.19
#6 · Parbhanicell 4890004710
distance 0.192
#7 · Parbhanicell 4890003474
distance 0.193
#8 · Parbhanicell 4890004427
distance 0.194
#9 · Parbhanicell 4890005108
distance 0.201
#10 · Parbhanicell 4890003842
distance 0.201
#11 · Jalnacell 4790000234
distance 0.202 · cross-district
#12 · Beedcell 4700007142
distance 0.203 · cross-district
#13 · Parbhanicell 4890003766
distance 0.205
#14 · Parbhanicell 4890004447
distance 0.206
#15 · Jalnacell 4790003607
distance 0.206 · cross-district
#16 · Parbhanicell 4890002339
distance 0.207
#17 · Buldhanacell 4720005530
distance 0.208 · cross-district
#18 · Parbhanicell 4890001926
distance 0.209
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":4890003749}}}'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.