Bhārata Strata · Maharashtra · Kolhapur · morphological twins
Places like cell 4800005983
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
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
42
morphology-v2 feature dimensions
Closest twin distance
0.098
lower = more alike (weighted)
The twins, closest first
#1 · Kolhapurcell 4800006335
distance 0.098
#2 · Kolhapurcell 4800005860
distance 0.128
#3 · Kolhapurcell 4800006348
distance 0.134
#4 · Kolhapurcell 4800006143
distance 0.153
#5 · Kolhapurcell 4800006142
distance 0.158
#6 · Kolhapurcell 4800006261
distance 0.16
#7 · Kolhapurcell 4800006028
distance 0.16
#8 · Ratnagiricell 4920002645
distance 0.162 · cross-district
#9 · Kolhapurcell 4800006303
distance 0.163
#10 · Kolhapurcell 4800006275
distance 0.168
#11 · Kolhapurcell 4800006319
distance 0.182
#12 · Kolhapurcell 4800005979
distance 0.189
#13 · Kolhapurcell 4800006274
distance 0.195
#14 · Kolhapurcell 4800006064
distance 0.197
#15 · Ratnagiricell 4920002381
distance 0.198 · cross-district
#16 · Ratnagiricell 4920002212
distance 0.204 · cross-district
#17 · Ratnagiricell 4920002489
distance 0.208 · cross-district
#18 · Kolhapurcell 4800005982
distance 0.209
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":4800005983}}}'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.