Bhārata Strata · Maharashtra · Nandurbar · morphological twins
Places like cell 4860001331
The MH-36 locality cells most similar to this Nandurbar 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 2 distinct districts
Index confidence
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.114
lower = more alike (weighted)
The twins, closest first
#1 · Dhulecell 4740004937
distance 0.114 · cross-district
#2 · Nandurbarcell 4860001436
distance 0.126
#3 · Nandurbarcell 4860001111
distance 0.143
#4 · Nandurbarcell 4860001435
distance 0.144
#5 · Nandurbarcell 4860001434
distance 0.145
#6 · Nandurbarcell 4860001386
distance 0.145
#7 · Nandurbarcell 4860001385
distance 0.15
#8 · Nandurbarcell 4860001064
distance 0.151
#9 · Nandurbarcell 4860001274
distance 0.154
#10 · Nandurbarcell 4860001496
distance 0.159
#11 · Dhulecell 4740003862
distance 0.167 · cross-district
#12 · Nandurbarcell 4860001007
distance 0.167
#13 · Nandurbarcell 4860001011
distance 0.169
#14 · Dhulecell 4740005070
distance 0.17 · cross-district
#15 · Nandurbarcell 4860001848
distance 0.173
#16 · Nandurbarcell 4860002026
distance 0.175
#17 · Nandurbarcell 4860001060
distance 0.178
#18 · Dhulecell 4740003611
distance 0.181 · 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":486,"cluster_id":4860001331}}}'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.