Bhārata Strata · Maharashtra · Raigad · morphological twins
Places like cell 4910004965
The MH-36 locality cells most similar to this Raigad 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 6 distinct districts
Index confidence
0.9
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.551
lower = more alike (weighted)
The twins, closest first
#1 · Mumbaicell 4820000052
distance 0.551 · cross-district
#2 · Raigadcell 4910004867
distance 0.573
#3 · Raigadcell 4910004919
distance 0.658
#4 · Raigadcell 4910004383
distance 0.661
#5 · Palgharcell 6650002136
distance 0.686 · cross-district
#6 · Raigadcell 4910004812
distance 0.691
#7 · Raigadcell 4910005117
distance 0.7
#8 · Raigadcell 4910004813
distance 0.701
#9 · Raigadcell 4910004918
distance 0.714
#10 · Raigadcell 4910004479
distance 0.721
#11 · Jalgaoncell 4780006194
distance 0.742 · cross-district
#12 · Raigadcell 4910004963
distance 0.747
#13 · Jalgaoncell 4780006497
distance 0.762 · cross-district
#14 · Mumbai Suburbancell 4830000235
distance 0.766 · cross-district
#15 · Raigadcell 4910004811
distance 0.768
#16 · Raigadcell 4910005109
distance 0.773
#17 · Raigadcell 4910004759
distance 0.786
#18 · Thanecell 4970000003
distance 0.792 · 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":491,"cluster_id":4910004965}}}'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.