Bhārata Strata · Maharashtra · Kolhapur · morphological twins
Places like cell 4800004715
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
0.139
lower = more alike (weighted)
The twins, closest first
#1 · Kolhapurcell 4800004369
distance 0.139
#2 · Kolhapurcell 4800004624
distance 0.15
#3 · Kolhapurcell 4800004286
distance 0.163
#4 · Sanglicell 4930002003
distance 0.166 · cross-district
#5 · Kolhapurcell 4800004890
distance 0.168
#6 · Kolhapurcell 4800005852
distance 0.177
#7 · Kolhapurcell 4800004045
distance 0.179
#8 · Kolhapurcell 4800004622
distance 0.182
#9 · Sanglicell 4930006199
distance 0.187 · cross-district
#10 · Kolhapurcell 4800004797
distance 0.193
#11 · Kolhapurcell 4800005311
distance 0.201
#12 · Kolhapurcell 4800004799
distance 0.204
#13 · Kolhapurcell 4800003673
distance 0.204
#14 · Punecell 4900000663
distance 0.206 · cross-district
#15 · Sanglicell 4930006392
distance 0.206 · cross-district
#16 · Kolhapurcell 4800003952
distance 0.207
#17 · Kolhapurcell 4800004533
distance 0.208
#18 · Punecell 4900001028
distance 0.209 · 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":4800004715}}}'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.