Bhārata Strata · Maharashtra · Amravati · morphological twins
Places like cell 4680002111
The MH-36 locality cells most similar to this Amravati 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
0.94
GUM mean confidence of the anchor (R24)
Dimensions compared
44
morphology-v2 feature dimensions
Closest twin distance
0.055
lower = more alike (weighted)
The twins, closest first
#1 · Amravaticell 4680001780
distance 0.055
#2 · Amravaticell 4680002216
distance 0.056
#3 · Akolacell 4670003572
distance 0.083 · cross-district
#4 · Amravaticell 4680002319
distance 0.086
#5 · Akolacell 4670003529
distance 0.096 · cross-district
#6 · Amravaticell 4680002424
distance 0.096
#7 · Akolacell 4670003611
distance 0.099 · cross-district
#8 · Amravaticell 4680002524
distance 0.101
#9 · Amravaticell 4680003230
distance 0.105
#10 · Amravaticell 4680003132
distance 0.107
#11 · Akolacell 4670003647
distance 0.107 · cross-district
#12 · Amravaticell 4680001890
distance 0.112
#13 · Akolacell 4670003720
distance 0.114 · cross-district
#14 · Amravaticell 4680002118
distance 0.116
#15 · Amravaticell 4680002217
distance 0.118
#16 · Amravaticell 4680002726
distance 0.121
#17 · Amravaticell 4680001783
distance 0.122
#18 · Amravaticell 4680002218
distance 0.129
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":468,"cluster_id":4680002111}}}'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.