Bhārata Strata · Maharashtra · Beed · morphological twins
Places like cell 4700000403
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 2 distinct districts
Index confidence
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
43
morphology-v2 feature dimensions
Closest twin distance
0.069
lower = more alike (weighted)
The twins, closest first
#1 · Beedcell 4700000934
distance 0.069
#2 · Beedcell 4700001199
distance 0.074
#3 · Beedcell 4700001196
distance 0.079
#4 · Dharashivcell 4880005568
distance 0.082 · cross-district
#5 · Beedcell 4700000051
distance 0.083
#6 · Beedcell 4700006010
distance 0.086
#7 · Dharashivcell 4880006152
distance 0.091 · cross-district
#8 · Beedcell 4700000126
distance 0.093
#9 · Dharashivcell 4880006004
distance 0.094 · cross-district
#10 · Beedcell 4700003971
distance 0.095
#11 · Dharashivcell 4880005663
distance 0.095 · cross-district
#12 · Beedcell 4700000692
distance 0.096
#13 · Dharashivcell 4880004621
distance 0.1 · cross-district
#14 · Beedcell 4700006295
distance 0.1
#15 · Beedcell 4700005276
distance 0.101
#16 · Beedcell 4700006296
distance 0.102
#17 · Dharashivcell 4880004707
distance 0.103 · cross-district
#18 · Dharashivcell 4880006081
distance 0.103 · 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":4700000403}}}'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.