Bhārata Strata · Maharashtra · Amravati · morphological twins
Places like cell 4680000855
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
0.072
lower = more alike (weighted)
The twins, closest first
#1 · Amravaticell 4680000924
distance 0.072
#2 · Amravaticell 4680001061
distance 0.083
#3 · Washimcell 4990004393
distance 0.084 · cross-district
#4 · Washimcell 4990004455
distance 0.084 · cross-district
#5 · Amravaticell 4680000997
distance 0.086
#6 · Amravaticell 4680000235
distance 0.09
#7 · Amravaticell 4680000595
distance 0.098
#8 · Amravaticell 4680001205
distance 0.099
#9 · Amravaticell 4680000862
distance 0.1
#10 · Amravaticell 4680000791
distance 0.101
#11 · Amravaticell 4680000877
distance 0.101
#12 · Amravaticell 4680000471
distance 0.103
#13 · Washimcell 4990004394
distance 0.105 · cross-district
#14 · Akolacell 4670001055
distance 0.106 · cross-district
#15 · Akolacell 4670001243
distance 0.106 · cross-district
#16 · Amravaticell 4680002373
distance 0.106
#17 · Amravaticell 4680000928
distance 0.108
#18 · Amravaticell 4680000876
distance 0.109
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":4680000855}}}'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.