Bhārata Strata · Maharashtra · Nashik · morphological twins
Places like cell 4870010203
The MH-36 locality cells most similar to this Nashik 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
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
43
morphology-v2 feature dimensions
Closest twin distance
0.343
lower = more alike (weighted)
The twins, closest first
#1 · Dhulecell 4740000375
distance 0.343 · cross-district
#2 · Nashikcell 4870010212
distance 0.351
#3 · Nandurbarcell 4860000903
distance 0.372 · cross-district
#4 · Nashikcell 4870010335
distance 0.38
#5 · Nandurbarcell 4860005028
distance 0.401 · cross-district
#6 · Nashikcell 4870009680
distance 0.402
#7 · Nandurbarcell 4860000847
distance 0.411 · cross-district
#8 · Nashikcell 4870009823
distance 0.414
#9 · Nashikcell 4870009941
distance 0.414
#10 · Dhulecell 4740005465
distance 0.424 · cross-district
#11 · Nashikcell 4870010470
distance 0.424
#12 · Nashikcell 4870010597
distance 0.425
#13 · Nashikcell 4870009417
distance 0.436
#14 · Nashikcell 4870010333
distance 0.437
#15 · Nashikcell 4870009949
distance 0.443
#16 · Nashikcell 4870009809
distance 0.448
#17 · Nashikcell 4870010080
distance 0.454
#18 · Wardhacell 4980003380
distance 0.46 · 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":487,"cluster_id":4870010203}}}'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.