Bhārata Strata · Maharashtra · Beed · morphological twins
Places like cell 4700003071
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 4 distinct districts
Index confidence
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
43
morphology-v2 feature dimensions
Closest twin distance
0.14
lower = more alike (weighted)
The twins, closest first
#1 · Beedcell 4700003070
distance 0.14
#2 · Beedcell 4700003248
distance 0.175
#3 · Nashikcell 4870006969
distance 0.18 · cross-district
#4 · Beedcell 4700003415
distance 0.183
#5 · Jalgaoncell 4780000007
distance 0.185 · cross-district
#6 · Beedcell 4700003240
distance 0.186
#7 · Jalgaoncell 4780000006
distance 0.192 · cross-district
#8 · Beedcell 4700003075
distance 0.201
#9 · Beedcell 4700003085
distance 0.205
#10 · Sanglicell 4930002715
distance 0.211 · cross-district
#11 · Nashikcell 4870006972
distance 0.213 · cross-district
#12 · Beedcell 4700003247
distance 0.213
#13 · Nashikcell 4870012510
distance 0.215 · cross-district
#14 · Nashikcell 4870012429
distance 0.215 · cross-district
#15 · Nashikcell 4870012509
distance 0.217 · cross-district
#16 · Beedcell 4700003588
distance 0.217
#17 · Beedcell 4700002892
distance 0.221
#18 · Beedcell 4700004283
distance 0.225
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":4700003071}}}'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.