Bhārata Strata · Maharashtra · Nandurbar · morphological twins
Places like cell 4860000278
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
0.189
lower = more alike (weighted)
The twins, closest first
#1 · Nandurbarcell 4860000234
distance 0.189
#2 · Nandurbarcell 4860000254
distance 0.206
#3 · Nandurbarcell 4860000441
distance 0.208
#4 · Nandurbarcell 4860000279
distance 0.22
#5 · Nandurbarcell 4860001228
distance 0.237
#6 · Nandurbarcell 4860000363
distance 0.239
#7 · Nandurbarcell 4860000297
distance 0.24
#8 · Dhulecell 4740005756
distance 0.248 · cross-district
#9 · Nandurbarcell 4860000207
distance 0.251
#10 · Dhulecell 4740005671
distance 0.251 · cross-district
#11 · Dhulecell 4740005753
distance 0.254 · cross-district
#12 · Nandurbarcell 4860000348
distance 0.255
#13 · Nandurbarcell 4860000226
distance 0.261
#14 · Nandurbarcell 4860000210
distance 0.266
#15 · Nandurbarcell 4860001227
distance 0.266
#16 · Dhulecell 4740005501
distance 0.267 · cross-district
#17 · Nandurbarcell 4860001173
distance 0.269
#18 · Nandurbarcell 4860001280
distance 0.274
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":4860000278}}}'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.