Bhārata Strata · Maharashtra · Kolhapur · morphological twins
Places like cell 4800000531
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
43
morphology-v2 feature dimensions
Closest twin distance
0.241
lower = more alike (weighted)
The twins, closest first
#1 · Kolhapurcell 4800000644
distance 0.241
#2 · Kolhapurcell 4800000399
distance 0.248
#3 · Kolhapurcell 4800000339
distance 0.255
#4 · Kolhapurcell 4800000720
distance 0.281
#5 · Kolhapurcell 4800000685
distance 0.283
#6 · Kolhapurcell 4800000403
distance 0.291
#7 · Kolhapurcell 4800001039
distance 0.298
#8 · Kolhapurcell 4800000400
distance 0.3
#9 · Ratnagiricell 4920006021
distance 0.305 · cross-district
#10 · Kolhapurcell 4800000715
distance 0.305
#11 · Ratnagiricell 4920004902
distance 0.306 · cross-district
#12 · Kolhapurcell 4800000684
distance 0.306
#13 · Kolhapurcell 4800001077
distance 0.306
#14 · Kolhapurcell 4800000606
distance 0.312
#15 · Kolhapurcell 4800000380
distance 0.315
#16 · Ratnagiricell 4920004510
distance 0.316 · cross-district
#17 · Ratnagiricell 4920006941
distance 0.318 · cross-district
#18 · Kolhapurcell 4800000347
distance 0.318
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":4800000531}}}'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.