Bhārata Strata · Maharashtra · Dhule · morphological twins
Places like cell 4740005448
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 7 distinct districts
Index confidence
0.93
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.271
lower = more alike (weighted)
The twins, closest first
#1 · Nashikcell 4870012922
distance 0.271 · cross-district
#2 · Yavatmalcell 5000001358
distance 0.297 · cross-district
#3 · Nandedcell 4850007267
distance 0.297 · cross-district
#4 · Dhulecell 4740005713
distance 0.306
#5 · Dhulecell 4740005824
distance 0.31
#6 · Dhulecell 4740005312
distance 0.315
#7 · Dhulecell 4740005787
distance 0.316
#8 · Dhulecell 4740005844
distance 0.316
#9 · Jalgaoncell 4780006605
distance 0.319 · cross-district
#10 · Dhulecell 4740005786
distance 0.32
#11 · Dhulecell 4740005372
distance 0.32
#12 · Dhulecell 4740005755
distance 0.32
#13 · Ahmednagarcell 4660004031
distance 0.321 · cross-district
#14 · Dhulecell 4740005903
distance 0.321
#15 · Washimcell 4990003002
distance 0.322 · cross-district
#16 · Jalgaoncell 4780004138
distance 0.322 · cross-district
#17 · Dhulecell 4740005554
distance 0.324
#18 · Dhulecell 4740005502
distance 0.326
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":4740005448}}}'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.