Bhārata Strata · Maharashtra · Amravati · morphological twins
Places like cell 4680004227
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 3 distinct districts
Index confidence
0.93
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.162
lower = more alike (weighted)
The twins, closest first
#1 · Amravaticell 4680004807
distance 0.162
#2 · Amravaticell 4680004146
distance 0.2
#3 · Amravaticell 4680004897
distance 0.205
#4 · Amravaticell 4680005005
distance 0.211
#5 · Amravaticell 4680005354
distance 0.213
#6 · Nagpurcell 4840007141
distance 0.214 · cross-district
#7 · Amravaticell 4680004612
distance 0.216
#8 · Nagpurcell 4840007032
distance 0.223 · cross-district
#9 · Nagpurcell 4840005441
distance 0.23 · cross-district
#10 · Amravaticell 4680004714
distance 0.239
#11 · Amravaticell 4680005595
distance 0.239
#12 · Amravaticell 4680004713
distance 0.24
#13 · Akolacell 4670004577
distance 0.245 · cross-district
#14 · Amravaticell 4680006295
distance 0.245
#15 · Amravaticell 4680005120
distance 0.245
#16 · Nagpurcell 4840006137
distance 0.246 · cross-district
#17 · Amravaticell 4680005233
distance 0.246
#18 · Amravaticell 4680005234
distance 0.248
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":4680004227}}}'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.