Bhārata Strata · Maharashtra · Thane · morphological twins
Places like cell 4970000328
The MH-36 locality cells most similar to this Thane 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 5 distinct districts
Index confidence
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.534
lower = more alike (weighted)
The twins, closest first
#1 · Thanecell 4970000718
distance 0.534
#2 · Thanecell 4970001120
distance 0.586
#3 · Thanecell 4970000280
distance 0.595
#4 · Thanecell 4970000645
distance 0.607
#5 · Raigadcell 4910000479
distance 0.65 · cross-district
#6 · Raigadcell 4910000680
distance 0.65 · cross-district
#7 · Mumbai Suburbancell 4830000153
distance 0.668 · cross-district
#8 · Thanecell 4970001212
distance 0.675
#9 · Raigadcell 4910000262
distance 0.695 · cross-district
#10 · Thanecell 4970000339
distance 0.708
#11 · Thanecell 4970001959
distance 0.71
#12 · Thanecell 4970001793
distance 0.718
#13 · Punecell 4900004759
distance 0.721 · cross-district
#14 · Thanecell 4970001547
distance 0.722
#15 · Raigadcell 4910005044
distance 0.735 · cross-district
#16 · Palgharcell 6650000013
distance 0.739 · cross-district
#17 · Thanecell 4970000791
distance 0.74
#18 · Thanecell 4970001213
distance 0.752
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":497,"cluster_id":4970000328}}}'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.