Bhārata Strata · Maharashtra · Dharashiv · morphological twins
Places like cell 4880001690
The MH-36 locality cells most similar to this Dharashiv 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
0.054
lower = more alike (weighted)
The twins, closest first
#1 · Dharashivcell 4880002312
distance 0.054
#2 · Dharashivcell 4880002488
distance 0.056
#3 · Dharashivcell 4880002532
distance 0.057
#4 · Dharashivcell 4880002328
distance 0.062
#5 · Dharashivcell 4880001334
distance 0.064
#6 · Laturcell 4810000751
distance 0.065 · cross-district
#7 · Laturcell 4810000436
distance 0.066 · cross-district
#8 · Dharashivcell 4880002019
distance 0.067
#9 · Dharashivcell 4880002255
distance 0.073
#10 · Laturcell 4810000491
distance 0.074 · cross-district
#11 · Dharashivcell 4880002495
distance 0.076
#12 · Dharashivcell 4880001495
distance 0.077
#13 · Dharashivcell 4880002489
distance 0.079
#14 · Dharashivcell 4880002253
distance 0.079
#15 · Dharashivcell 4880001592
distance 0.08
#16 · Laturcell 4810000621
distance 0.08 · cross-district
#17 · Dharashivcell 4880001333
distance 0.081
#18 · Dharashivcell 4880001327
distance 0.083
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":488,"cluster_id":4880001690}}}'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.