Bhārata Strata · Maharashtra · Kolhapur · morphological twins
Places like cell 4800004813
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
42
morphology-v2 feature dimensions
Closest twin distance
0.222
lower = more alike (weighted)
The twins, closest first
#1 · Kolhapurcell 4800004899
distance 0.222
#2 · Kolhapurcell 4800004814
distance 0.231
#3 · Kolhapurcell 4800005582
distance 0.3
#4 · Kolhapurcell 4800002979
distance 0.308
#5 · Kolhapurcell 4800006029
distance 0.309
#6 · Kolhapurcell 4800005160
distance 0.314
#7 · Ratnagiricell 4920001052
distance 0.322 · cross-district
#8 · Kolhapurcell 4800005795
distance 0.325
#9 · Kolhapurcell 4800006394
distance 0.326
#10 · Ratnagiricell 4920002923
distance 0.328 · cross-district
#11 · Ratnagiricell 4920002877
distance 0.332 · cross-district
#12 · Kolhapurcell 4800003019
distance 0.333
#13 · Ratnagiricell 4920000751
distance 0.334 · cross-district
#14 · Kolhapurcell 4800006166
distance 0.335
#15 · Kolhapurcell 4800006030
distance 0.335
#16 · Kolhapurcell 4800006408
distance 0.336
#17 · Kolhapurcell 4800006395
distance 0.337
#18 · Kolhapurcell 4800002796
distance 0.337
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":4800004813}}}'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.