Bhārata Strata · Maharashtra · Palghar · morphological twins
Places like cell 6650003652
The MH-36 locality cells most similar to this Palghar 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
0.9
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.293
lower = more alike (weighted)
The twins, closest first
#1 · Palgharcell 6650000139
distance 0.293
#2 · Palgharcell 6650000125
distance 0.315
#3 · Mumbai Suburbancell 4830000234
distance 0.32 · cross-district
#4 · Thanecell 4970001290
distance 0.32 · cross-district
#5 · Palgharcell 6650000310
distance 0.332
#6 · Palgharcell 6650000066
distance 0.341
#7 · Thanecell 4970001292
distance 0.344 · cross-district
#8 · Palgharcell 6650000163
distance 0.35
#9 · Mumbai Suburbancell 4830000328
distance 0.373 · cross-district
#10 · Palgharcell 6650001677
distance 0.374
#11 · Palgharcell 6650002747
distance 0.379
#12 · Palgharcell 6650000048
distance 0.391
#13 · Palgharcell 6650000911
distance 0.395
#14 · Palgharcell 6650000237
distance 0.404
#15 · Palgharcell 6650000160
distance 0.404
#16 · Palgharcell 6650003723
distance 0.405
#17 · Thanecell 4970001198
distance 0.407 · cross-district
#18 · Palgharcell 6650004387
distance 0.41
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":665,"cluster_id":6650003652}}}'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.