Bhārata Strata · Maharashtra · Beed · morphological twins
Places like cell 4700006262
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
0.168
lower = more alike (weighted)
The twins, closest first
#1 · Beedcell 4700005693
distance 0.168
#2 · Nandedcell 4850000677
distance 0.19 · cross-district
#3 · Beedcell 4700004930
distance 0.228
#4 · Sanglicell 4930003120
distance 0.231 · cross-district
#5 · Beedcell 4700005403
distance 0.232
#6 · Beedcell 4700005962
distance 0.239
#7 · Beedcell 4700005974
distance 0.244
#8 · Beedcell 4700005836
distance 0.244
#9 · Beedcell 4700006684
distance 0.248
#10 · Sanglicell 4930003441
distance 0.251 · cross-district
#11 · Sanglicell 4930006371
distance 0.253 · cross-district
#12 · Beedcell 4700006810
distance 0.254
#13 · Nandedcell 4850000766
distance 0.259 · cross-district
#14 · Sanglicell 4930004714
distance 0.261 · cross-district
#15 · Nandedcell 4850000636
distance 0.262 · cross-district
#16 · Beedcell 4700001263
distance 0.263
#17 · Beedcell 4700005952
distance 0.263
#18 · Jalnacell 4790001117
distance 0.265 · 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":4700006262}}}'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.