Bhārata Strata · Maharashtra · Dhule · morphological twins
Places like cell 4740002083
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 5 distinct districts
Index confidence
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.138
lower = more alike (weighted)
The twins, closest first
#1 · Dhulecell 4740000405
distance 0.138
#2 · Dhulecell 4740000377
distance 0.142
#3 · Dhulecell 4740001874
distance 0.143
#4 · Dhulecell 4740001157
distance 0.154
#5 · Dhulecell 4740001155
distance 0.174
#6 · Nandedcell 4850003756
distance 0.183 · cross-district
#7 · Beedcell 4700008148
distance 0.185 · cross-district
#8 · Dhulecell 4740000439
distance 0.189
#9 · Beedcell 4700006659
distance 0.19 · cross-district
#10 · Dhulecell 4740000969
distance 0.191
#11 · Sanglicell 4930002907
distance 0.195 · cross-district
#12 · Dhulecell 4740000442
distance 0.195
#13 · Beedcell 4700007964
distance 0.196 · cross-district
#14 · Nashikcell 4870005631
distance 0.196 · cross-district
#15 · Dhulecell 4740003189
distance 0.197
#16 · Beedcell 4700007751
distance 0.198 · cross-district
#17 · Dhulecell 4740002792
distance 0.2
#18 · Nandedcell 4850004050
distance 0.2 · 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":474,"cluster_id":4740002083}}}'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.