Bhārata Strata · Maharashtra · Dhule · morphological twins
Places like cell 4740002540
The MH-36 locality cells most similar to this Dhule 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
45
morphology-v2 feature dimensions
Closest twin distance
0.217
lower = more alike (weighted)
The twins, closest first
#1 · Dhulecell 4740000558
distance 0.217
#2 · Dhulecell 4740001086
distance 0.226
#3 · Nashikcell 4870011705
distance 0.251 · cross-district
#4 · Dhulecell 4740002541
distance 0.251
#5 · Jalgaoncell 4780000343
distance 0.256 · cross-district
#6 · Dhulecell 4740000972
distance 0.269
#7 · Nashikcell 4870012947
distance 0.271 · cross-district
#8 · Dhulecell 4740002829
distance 0.273
#9 · Dhulecell 4740002222
distance 0.277
#10 · Ahmednagarcell 4660013854
distance 0.28 · cross-district
#11 · Dhulecell 4740000353
distance 0.28
#12 · Dhulecell 4740001386
distance 0.283
#13 · Jalgaoncell 4780001550
distance 0.283 · cross-district
#14 · Dhulecell 4740002634
distance 0.284
#15 · Nashikcell 4870011600
distance 0.284 · cross-district
#16 · Dhulecell 4740003006
distance 0.285
#17 · Nashikcell 4870007080
distance 0.285 · cross-district
#18 · Dhulecell 4740003100
distance 0.287
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":474,"cluster_id":4740002540}}}'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.