Bhārata Strata · Maharashtra · Pune · morphological twins
Places like cell 4900007457
The MH-36 locality cells most similar to this Pune 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
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.395
lower = more alike (weighted)
The twins, closest first
#1 · Punecell 4900006968
distance 0.395
#2 · Punecell 4900005855
distance 0.467
#3 · Punecell 4900005726
distance 0.639
#4 · Punecell 4900005730
distance 0.651
#5 · Punecell 4900006967
distance 0.791
#6 · Punecell 4900007456
distance 0.792
#7 · Nashikcell 4870002718
distance 0.81 · cross-district
#8 · Punecell 4900005589
distance 0.898
#9 · Nashikcell 4870002602
distance 0.916 · cross-district
#10 · Nashikcell 4870002716
distance 0.942 · cross-district
#11 · Punecell 4900010259
distance 0.944
#12 · Nashikcell 4870002505
distance 0.951 · cross-district
#13 · Nashikcell 4870003098
distance 0.954 · cross-district
#14 · Punecell 4900005721
distance 0.955
#15 · Nashikcell 4870002417
distance 0.979 · cross-district
#16 · Nashikcell 4870002611
distance 0.984 · cross-district
#17 · Punecell 4900006115
distance 0.986
#18 · Nashikcell 4870002608
distance 0.988 · cross-district
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":490,"cluster_id":4900007457}}}'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.