Bhārata Strata · Maharashtra · Kolhapur · morphological twins
Places like cell 4800003530
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
0.111
lower = more alike (weighted)
The twins, closest first
#1 · Kolhapurcell 4800003591
distance 0.111
#2 · Kolhapurcell 4800003588
distance 0.135
#3 · Kolhapurcell 4800003471
distance 0.139
#4 · Kolhapurcell 4800003407
distance 0.142
#5 · Kolhapurcell 4800003355
distance 0.153
#6 · Kolhapurcell 4800003046
distance 0.178
#7 · Sataracell 4940003291
distance 0.185 · cross-district
#8 · Kolhapurcell 4800003527
distance 0.19
#9 · Kolhapurcell 4800003304
distance 0.199
#10 · Kolhapurcell 4800003178
distance 0.203
#11 · Kolhapurcell 4800003268
distance 0.208
#12 · Punecell 4900002657
distance 0.209 · cross-district
#13 · Kolhapurcell 4800002920
distance 0.211
#14 · Kolhapurcell 4800003547
distance 0.217
#15 · Sataracell 4940003056
distance 0.217 · cross-district
#16 · Kolhapurcell 4800003138
distance 0.222
#17 · Sataracell 4940005354
distance 0.223 · cross-district
#18 · Punecell 4900001318
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":4800003530}}}'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.