Bhārata Strata · Maharashtra · Dhule · morphological twins
Places like cell 4740004475
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
0.077
lower = more alike (weighted)
The twins, closest first
#1 · Dhulecell 4740004606
distance 0.077
#2 · Dhulecell 4740004477
distance 0.081
#3 · Dhulecell 4740004402
distance 0.089
#4 · Jalgaoncell 4780007274
distance 0.096 · cross-district
#5 · Dhulecell 4740004543
distance 0.104
#6 · Jalgaoncell 4780007396
distance 0.109 · cross-district
#7 · Dhulecell 4740004788
distance 0.109
#8 · Jalgaoncell 4780007521
distance 0.114 · cross-district
#9 · Dhulecell 4740004544
distance 0.114
#10 · Dhulecell 4740004142
distance 0.115
#11 · Jalgaoncell 4780006901
distance 0.119 · cross-district
#12 · Jalgaoncell 4780007395
distance 0.12 · cross-district
#13 · Jalgaoncell 4780004799
distance 0.12 · cross-district
#14 · Dhulecell 4740004479
distance 0.12
#15 · Dhulecell 4740004666
distance 0.124
#16 · Dhulecell 4740005575
distance 0.129
#17 · Jalgaoncell 4780006918
distance 0.131 · cross-district
#18 · Dhulecell 4740004227
distance 0.131
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":4740004475}}}'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.