Bhārata Strata · Maharashtra · Thane · morphological twins
Places like cell 4970000609
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 3 distinct districts
Index confidence
0.89
GUM mean confidence of the anchor (R24)
Dimensions compared
44
morphology-v2 feature dimensions
Closest twin distance
0.335
lower = more alike (weighted)
The twins, closest first
#1 · Thanecell 4970000481
distance 0.335
#2 · Thanecell 4970000486
distance 0.394
#3 · Thanecell 4970000679
distance 0.398
#4 · Thanecell 4970000681
distance 0.466
#5 · Thanecell 4970001009
distance 0.518
#6 · Thanecell 4970000545
distance 0.525
#7 · Punecell 4900012432
distance 0.527 · cross-district
#8 · Raigadcell 4910005086
distance 0.529 · cross-district
#9 · Punecell 4900004191
distance 0.549 · cross-district
#10 · Thanecell 4970000548
distance 0.558
#11 · Thanecell 4970000426
distance 0.58
#12 · Thanecell 4970000429
distance 0.591
#13 · Punecell 4900012720
distance 0.596 · cross-district
#14 · Thanecell 4970000487
distance 0.599
#15 · Raigadcell 4910005286
distance 0.612 · cross-district
#16 · Punecell 4900004613
distance 0.613 · cross-district
#17 · Punecell 4900004342
distance 0.623 · cross-district
#18 · Punecell 4900004330
distance 0.629 · 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":4970000609}}}'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.