Bhārata Strata · Maharashtra · Kolhapur · morphological twins
Places like cell 4800003088
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
0.176
lower = more alike (weighted)
The twins, closest first
#1 · Kolhapurcell 4800002690
distance 0.176
#2 · Kolhapurcell 4800002913
distance 0.202
#3 · Kolhapurcell 4800002637
distance 0.21
#4 · Sataracell 4940001657
distance 0.218 · cross-district
#5 · Kolhapurcell 4800003228
distance 0.22
#6 · Sataracell 4940001564
distance 0.22 · cross-district
#7 · Sataracell 4940001117
distance 0.222 · cross-district
#8 · Kolhapurcell 4800003002
distance 0.222
#9 · Sataracell 4940001571
distance 0.224 · cross-district
#10 · Kolhapurcell 4800002692
distance 0.228
#11 · Kolhapurcell 4800002590
distance 0.233
#12 · Kolhapurcell 4800002591
distance 0.235
#13 · Punecell 4900001727
distance 0.235 · cross-district
#14 · Kolhapurcell 4800002879
distance 0.235
#15 · Kolhapurcell 4800003581
distance 0.239
#16 · Kolhapurcell 4800002737
distance 0.239
#17 · Kolhapurcell 4800002925
distance 0.239
#18 · Kolhapurcell 4800002685
distance 0.241
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":4800003088}}}'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.