Bhārata Strata · Maharashtra · Kolhapur · morphological twins
Places like cell 4800006404
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 2 distinct districts
Index confidence
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
42
morphology-v2 feature dimensions
Closest twin distance
0.121
lower = more alike (weighted)
The twins, closest first
#1 · Kolhapurcell 4800006063
distance 0.121
#2 · Kolhapurcell 4800006116
distance 0.129
#3 · Kolhapurcell 4800006091
distance 0.131
#4 · Kolhapurcell 4800006417
distance 0.136
#5 · Kolhapurcell 4800006403
distance 0.147
#6 · Kolhapurcell 4800005979
distance 0.15
#7 · Kolhapurcell 4800005980
distance 0.151
#8 · Kolhapurcell 4800006142
distance 0.156
#9 · Kolhapurcell 4800006064
distance 0.157
#10 · Kolhapurcell 4800006090
distance 0.162
#11 · Kolhapurcell 4800006066
distance 0.162
#12 · Kolhapurcell 4800006026
distance 0.168
#13 · Ratnagiricell 4920002647
distance 0.17 · cross-district
#14 · Ratnagiricell 4920002801
distance 0.178 · cross-district
#15 · Kolhapurcell 4800006143
distance 0.188
#16 · Kolhapurcell 4800005981
distance 0.188
#17 · Ratnagiricell 4920002751
distance 0.192 · cross-district
#18 · Ratnagiricell 4920002645
distance 0.193 · 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":480,"cluster_id":4800006404}}}'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.