Bhārata Strata · Maharashtra · Sindhudurg · morphological twins
Places like cell 4950003339
The MH-36 locality cells most similar to this Sindhudurg 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
44
morphology-v2 feature dimensions
Closest twin distance
0.275
lower = more alike (weighted)
The twins, closest first
#1 · Sindhudurgcell 4950003197
distance 0.275
#2 · Sindhudurgcell 4950000584
distance 0.284
#3 · Sindhudurgcell 4950000678
distance 0.303
#4 · Sindhudurgcell 4950002499
distance 0.305
#5 · Sindhudurgcell 4950002909
distance 0.306
#6 · Sindhudurgcell 4950000768
distance 0.314
#7 · Sindhudurgcell 4950000532
distance 0.314
#8 · Sindhudurgcell 4950003244
distance 0.316
#9 · Sindhudurgcell 4950000579
distance 0.318
#10 · Sindhudurgcell 4950002307
distance 0.326
#11 · Kolhapurcell 4800002502
distance 0.328 · cross-district
#12 · Sindhudurgcell 4950002760
distance 0.328
#13 · Sindhudurgcell 4950000065
distance 0.329
#14 · Sindhudurgcell 4950002448
distance 0.331
#15 · Kolhapurcell 4800000118
distance 0.332 · cross-district
#16 · Sindhudurgcell 4950003338
distance 0.334
#17 · Sindhudurgcell 4950003051
distance 0.335
#18 · Sindhudurgcell 4950002303
distance 0.337
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":495,"cluster_id":4950003339}}}'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.