Bhārata Strata · Maharashtra · Kolhapur · morphological twins
Places like cell 4800003546
The MH-36 locality cells most similar to this Kolhapur 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
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
42
morphology-v2 feature dimensions
Closest twin distance
0.122
lower = more alike (weighted)
The twins, closest first
#1 · Kolhapurcell 4800003551
distance 0.122
#2 · Kolhapurcell 4800003674
distance 0.148
#3 · Kolhapurcell 4800003608
distance 0.164
#4 · Kolhapurcell 4800003549
distance 0.181
#5 · Sanglicell 4930004232
distance 0.192 · cross-district
#6 · Kolhapurcell 4800003430
distance 0.194
#7 · Kolhapurcell 4800003550
distance 0.2
#8 · Kolhapurcell 4800003681
distance 0.207
#9 · Kolhapurcell 4800003545
distance 0.209
#10 · Sanglicell 4930000286
distance 0.22 · cross-district
#11 · Kolhapurcell 4800003675
distance 0.221
#12 · Kolhapurcell 4800003894
distance 0.223
#13 · Punecell 4900004033
distance 0.226 · cross-district
#14 · Solapurcell 4960011458
distance 0.229 · cross-district
#15 · Sanglicell 4930004237
distance 0.235 · cross-district
#16 · Kolhapurcell 4800003488
distance 0.239
#17 · Kolhapurcell 4800004542
distance 0.24
#18 · Kolhapurcell 4800003814
distance 0.241
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":480,"cluster_id":4800003546}}}'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.