Bhārata Strata · Maharashtra · Kolhapur · morphological twins
Places like cell 4800003806
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 5 distinct districts
Index confidence
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
43
morphology-v2 feature dimensions
Closest twin distance
0.19
lower = more alike (weighted)
The twins, closest first
#1 · Kolhapurcell 4800005228
distance 0.19
#2 · Kolhapurcell 4800004879
distance 0.238
#3 · Kolhapurcell 4800004957
distance 0.251
#4 · Kolhapurcell 4800005718
distance 0.257
#5 · Kolhapurcell 4800004607
distance 0.261
#6 · Kolhapurcell 4800005134
distance 0.263
#7 · Kolhapurcell 4800003795
distance 0.266
#8 · Kolhapurcell 4800003781
distance 0.281
#9 · Beedcell 4700005256
distance 0.283 · cross-district
#10 · Sataracell 4940004709
distance 0.283 · cross-district
#11 · Sataracell 4940005079
distance 0.285 · cross-district
#12 · Akolacell 4670002308
distance 0.287 · cross-district
#13 · Kolhapurcell 4800005047
distance 0.288
#14 · Sanglicell 4930002000
distance 0.292 · cross-district
#15 · Kolhapurcell 4800005401
distance 0.294
#16 · Kolhapurcell 4800004610
distance 0.296
#17 · Kolhapurcell 4800003877
distance 0.296
#18 · Kolhapurcell 4800003807
distance 0.296
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":4800003806}}}'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.