Bhārata Strata · Maharashtra · Thane · morphological twins
Places like cell 4970002931
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 7 distinct districts
Index confidence
0.9
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.385
lower = more alike (weighted)
The twins, closest first
#1 · Thanecell 4970002694
distance 0.385
#2 · Thanecell 4970003025
distance 0.441
#3 · Thanecell 4970002866
distance 0.476
#4 · Thanecell 4970002511
distance 0.478
#5 · Thanecell 4970003195
distance 0.508
#6 · Thanecell 4970002270
distance 0.51
#7 · Thanecell 4970002978
distance 0.515
#8 · Thanecell 4970002878
distance 0.525
#9 · Thanecell 4970002226
distance 0.529
#10 · Thanecell 4970001873
distance 0.53
#11 · Ratnagiricell 4920004847
distance 0.537 · cross-district
#12 · Thanecell 4970001789
distance 0.537
#13 · Bhandaracell 4710003538
distance 0.543 · cross-district
#14 · Palgharcell 6650000757
distance 0.547 · cross-district
#15 · Palgharcell 6650000761
distance 0.563 · cross-district
#16 · Sataracell 4940002036
distance 0.572 · cross-district
#17 · Nashikcell 4870008141
distance 0.572 · cross-district
#18 · Raigadcell 4910000832
distance 0.573 · 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":4970002931}}}'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.