Bhārata Strata · Maharashtra · Beed · morphological twins
Places like cell 4700003213
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 5 distinct districts
Index confidence
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
42
morphology-v2 feature dimensions
Closest twin distance
0.125
lower = more alike (weighted)
The twins, closest first
#1 · Beedcell 4700003385
distance 0.125
#2 · Beedcell 4700004034
distance 0.157
#3 · Beedcell 4700003206
distance 0.163
#4 · Nashikcell 4870013300
distance 0.166 · cross-district
#5 · Beedcell 4700003205
distance 0.168
#6 · Beedcell 4700003374
distance 0.171
#7 · Nashikcell 4870013301
distance 0.176 · cross-district
#8 · Beedcell 4700004208
distance 0.177
#9 · Nashikcell 4870013238
distance 0.19 · cross-district
#10 · Beedcell 4700004052
distance 0.19
#11 · Beedcell 4700003549
distance 0.192
#12 · Beedcell 4700003415
distance 0.193
#13 · Beedcell 4700004456
distance 0.199
#14 · Beedcell 4700004246
distance 0.201
#15 · Dhulecell 4740000468
distance 0.203 · cross-district
#16 · Nashikcell 4870013240
distance 0.203 · cross-district
#17 · Chhatrapati Sambhajinagarcell 4690007079
distance 0.203 · cross-district
#18 · Jalgaoncell 4780006868
distance 0.204 · 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":4700003213}}}'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.