Bhārata Strata · Maharashtra · Kolhapur · morphological twins
Places like cell 4800001683
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 3 distinct districts
Index confidence
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
43
morphology-v2 feature dimensions
Closest twin distance
0.149
lower = more alike (weighted)
The twins, closest first
#1 · Kolhapurcell 4800002493
distance 0.149
#2 · Kolhapurcell 4800002264
distance 0.157
#3 · Kolhapurcell 4800001461
distance 0.169
#4 · Kolhapurcell 4800001575
distance 0.172
#5 · Kolhapurcell 4800001520
distance 0.181
#6 · Kolhapurcell 4800002007
distance 0.189
#7 · Kolhapurcell 4800001798
distance 0.195
#8 · Kolhapurcell 4800001402
distance 0.203
#9 · Kolhapurcell 4800002540
distance 0.206
#10 · Kolhapurcell 4800001630
distance 0.206
#11 · Ahmednagarcell 4660004210
distance 0.212 · cross-district
#12 · Kolhapurcell 4800002127
distance 0.213
#13 · Kolhapurcell 4800002062
distance 0.216
#14 · Beedcell 4700003679
distance 0.22 · cross-district
#15 · Kolhapurcell 4800002109
distance 0.221
#16 · Beedcell 4700004717
distance 0.224 · cross-district
#17 · Beedcell 4700004360
distance 0.224 · cross-district
#18 · Beedcell 4700004888
distance 0.226 · 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":4800001683}}}'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.