Bhārata Strata · Maharashtra · Pune · morphological twins
Places like cell 4900007456
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
0.592
lower = more alike (weighted)
The twins, closest first
#1 · Punecell 4900005730
distance 0.592
#2 · Punecell 4900006968
distance 0.623
#3 · Punecell 4900006967
distance 0.66
#4 · Nashikcell 4870002715
distance 0.674 · cross-district
#5 · Punecell 4900006844
distance 0.683
#6 · Punecell 4900005855
distance 0.69
#7 · Punecell 4900007334
distance 0.691
#8 · Punecell 4900006841
distance 0.695
#9 · Nashikcell 4870002509
distance 0.772 · cross-district
#10 · Punecell 4900007457
distance 0.792
#11 · Punecell 4900008507
distance 0.804
#12 · Nashikcell 4870003232
distance 0.804 · cross-district
#13 · Nashikcell 4870002718
distance 0.805 · cross-district
#14 · Nashikcell 4870002602
distance 0.807 · cross-district
#15 · Nashikcell 4870003090
distance 0.812 · cross-district
#16 · Punecell 4900007093
distance 0.816
#17 · Nashikcell 4870002716
distance 0.824 · cross-district
#18 · Nashikcell 4870003098
distance 0.836 · 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":4900007456}}}'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.