Bhārata Strata · Maharashtra · Dhule · morphological twins
Places like cell 4740000768
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
0.192
lower = more alike (weighted)
The twins, closest first
#1 · Dhulecell 4740001076
distance 0.192
#2 · Dhulecell 4740000044
distance 0.223
#3 · Dhulecell 4740000220
distance 0.225
#4 · Ahmednagarcell 4660007613
distance 0.227 · cross-district
#5 · Jalgaoncell 4780004428
distance 0.233 · cross-district
#6 · Nashikcell 4870012048
distance 0.236 · cross-district
#7 · Dhulecell 4740000281
distance 0.245
#8 · Dhulecell 4740001160
distance 0.25
#9 · Nashikcell 4870011802
distance 0.252 · cross-district
#10 · Dhulecell 4740000382
distance 0.255
#11 · Nashikcell 4870012036
distance 0.263 · cross-district
#12 · Dhulecell 4740001476
distance 0.264
#13 · Nashikcell 4870006784
distance 0.272 · cross-district
#14 · Dhulecell 4740000880
distance 0.281
#15 · Dhulecell 4740004685
distance 0.284
#16 · Nashikcell 4870011689
distance 0.286 · cross-district
#17 · Dhulecell 4740000242
distance 0.291
#18 · Dhulecell 4740000241
distance 0.292
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":4740000768}}}'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.