Bhārata Strata · Maharashtra · Beed · morphological twins
Places like cell 4700000323
The MH-36 locality cells most similar to this Beed 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 7 distinct districts
Index confidence
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
43
morphology-v2 feature dimensions
Closest twin distance
0.12
lower = more alike (weighted)
The twins, closest first
#1 · Beedcell 4700002729
distance 0.12
#2 · Laturcell 4810002410
distance 0.125 · cross-district
#3 · Beedcell 4700001458
distance 0.153
#4 · Beedcell 4700000265
distance 0.165
#5 · Beedcell 4700004994
distance 0.168
#6 · Solapurcell 4960001547
distance 0.171 · cross-district
#7 · Jalnacell 4790001111
distance 0.176 · cross-district
#8 · Beedcell 4700001291
distance 0.179
#9 · Dharashivcell 4880000061
distance 0.18 · cross-district
#10 · Sanglicell 4930000485
distance 0.18 · cross-district
#11 · Beedcell 4700001317
distance 0.18
#12 · Buldhanacell 4720001178
distance 0.184 · cross-district
#13 · Beedcell 4700000579
distance 0.186
#14 · Buldhanacell 4720001316
distance 0.187 · cross-district
#15 · Beedcell 4700002562
distance 0.188
#16 · Beedcell 4700002066
distance 0.189
#17 · Beedcell 4700000321
distance 0.19
#18 · Laturcell 4810004005
distance 0.19 · 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":470,"cluster_id":4700000323}}}'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.