Bhārata Strata · Maharashtra · Thane · morphological twins
Places like cell 4970001139
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 4 distinct districts
Index confidence
0.91
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.296
lower = more alike (weighted)
The twins, closest first
#1 · Thanecell 4970000874
distance 0.296
#2 · Thanecell 4970000717
distance 0.407
#3 · Bhandaracell 4710002021
distance 0.445 · cross-district
#4 · Thanecell 4970001127
distance 0.445
#5 · Thanecell 4970000801
distance 0.467
#6 · Thanecell 4970000578
distance 0.467
#7 · Thanecell 4970000651
distance 0.491
#8 · Thanecell 4970000512
distance 0.494
#9 · Thanecell 4970001299
distance 0.501
#10 · Thanecell 4970000723
distance 0.512
#11 · Mumbai Suburbancell 4830000187
distance 0.513 · cross-district
#12 · Thanecell 4970001380
distance 0.513
#13 · Sataracell 4940005677
distance 0.522 · cross-district
#14 · Mumbai Suburbancell 4830000193
distance 0.537 · cross-district
#15 · Bhandaracell 4710002135
distance 0.589 · cross-district
#16 · Thanecell 4970000960
distance 0.594
#17 · Thanecell 4970001301
distance 0.601
#18 · Sataracell 4940005562
distance 0.612 · 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":497,"cluster_id":4970001139}}}'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.