Bhārata Strata · Maharashtra · Dhule · morphological twins
Places like cell 4740004463
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 2 distinct districts
Index confidence
0.92
GUM mean confidence of the anchor (R24)
Dimensions compared
45
morphology-v2 feature dimensions
Closest twin distance
0.043
lower = more alike (weighted)
The twins, closest first
#1 · Dhulecell 4740004391
distance 0.043
#2 · Dhulecell 4740004311
distance 0.083
#3 · Dhulecell 4740004312
distance 0.086
#4 · Dhulecell 4740004054
distance 0.09
#5 · Dhulecell 4740004228
distance 0.092
#6 · Dhulecell 4740004530
distance 0.095
#7 · Dhulecell 4740004465
distance 0.099
#8 · Jalgaoncell 4780005849
distance 0.109 · cross-district
#9 · Jalgaoncell 4780007876
distance 0.11 · cross-district
#10 · Dhulecell 4740004389
distance 0.111
#11 · Jalgaoncell 4780007029
distance 0.115 · cross-district
#12 · Jalgaoncell 4780007768
distance 0.116 · cross-district
#13 · Dhulecell 4740004053
distance 0.118
#14 · Jalgaoncell 4780007391
distance 0.118 · cross-district
#15 · Dhulecell 4740004642
distance 0.119
#16 · Dhulecell 4740004532
distance 0.12
#17 · Jalgaoncell 4780006756
distance 0.125 · cross-district
#18 · Jalgaoncell 4780007039
distance 0.128 · 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":4740004463}}}'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.