Bhārata Strata · Maharashtra · Sangli · morphological twins
Places like cell 4930002146
The MH-36 locality cells most similar to this Sangli 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 3 distinct districts
Index confidence
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.185
lower = more alike (weighted)
The twins, closest first
#1 · Sanglicell 4930002147
distance 0.185
#2 · Sanglicell 4930002483
distance 0.204
#3 · Sanglicell 4930002487
distance 0.206
#4 · Sanglicell 4930002484
distance 0.207
#5 · Sanglicell 4930002655
distance 0.219
#6 · Sanglicell 4930000993
distance 0.244
#7 · Kolhapurcell 4800006005
distance 0.245 · cross-district
#8 · Kolhapurcell 4800006006
distance 0.247 · cross-district
#9 · Sanglicell 4930001978
distance 0.252
#10 · Kolhapurcell 4800006000
distance 0.255 · cross-district
#11 · Sanglicell 4930001982
distance 0.262
#12 · Kolhapurcell 4800006003
distance 0.266 · cross-district
#13 · Sanglicell 4930003157
distance 0.27
#14 · Sanglicell 4930002141
distance 0.274
#15 · Sanglicell 4930002822
distance 0.28
#16 · Sanglicell 4930002476
distance 0.282
#17 · Kolhapurcell 4800006251
distance 0.286 · cross-district
#18 · Nashikcell 4870013350
distance 0.288 · 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":493,"cluster_id":4930002146}}}'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.