Bhārata Strata · Maharashtra · Kolhapur · morphological twins
Places like cell 4800004030
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
43
morphology-v2 feature dimensions
Closest twin distance
0.108
lower = more alike (weighted)
The twins, closest first
#1 · Kolhapurcell 4800004107
distance 0.108
#2 · Kolhapurcell 4800004613
distance 0.136
#3 · Kolhapurcell 4800004271
distance 0.138
#4 · Kolhapurcell 4800004708
distance 0.166
#5 · Kolhapurcell 4800004520
distance 0.169
#6 · Kolhapurcell 4800004971
distance 0.174
#7 · Kolhapurcell 4800004436
distance 0.175
#8 · Sanglicell 4930000384
distance 0.181 · cross-district
#9 · Kolhapurcell 4800004038
distance 0.191
#10 · Kolhapurcell 4800003959
distance 0.197
#11 · Kolhapurcell 4800005045
distance 0.2
#12 · Kolhapurcell 4800005304
distance 0.203
#13 · Punecell 4900001008
distance 0.209 · cross-district
#14 · Solapurcell 4960009278
distance 0.212 · cross-district
#15 · Kolhapurcell 4800004886
distance 0.219
#16 · Sanglicell 4930000793
distance 0.222 · cross-district
#17 · Kolhapurcell 4800004878
distance 0.223
#18 · Punecell 4900004180
distance 0.223 · 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":4800004030}}}'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.