Bhārata Strata · Maharashtra · Nashik · morphological twins

Places like cell 4870010751

The MH-36 locality cells most similar to this Nashik 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

across 2 distinct districts

Index confidence

0.9

GUM mean confidence of the anchor (R24)

Dimensions compared

morphology-v2 feature dimensions

Closest twin distance

0.139

lower = more alike (weighted)

The twins, closest first

#1 · Nashikcell 4870008733

distance 0.139

#2 · Nashikcell 4870009837

distance 0.16

#3 · Nashikcell 4870011133

distance 0.167

#4 · Nashikcell 4870009288

distance 0.179

#5 · Nashikcell 4870010616

distance 0.186

#6 · Nashikcell 4870009154

distance 0.187

#7 · Nashikcell 4870011013

distance 0.19

#8 · Nashikcell 4870011261

distance 0.19

#9 · Nashikcell 4870012264

distance 0.19

#10 · Nashikcell 4870011492

distance 0.206

#11 · Thanecell 4970003101

distance 0.219 · cross-district

#12 · Nashikcell 4870011382

distance 0.22

#13 · Nashikcell 4870008734

distance 0.22

#14 · Nashikcell 4870008732

distance 0.22

#15 · Nashikcell 4870012070

distance 0.224

#16 · Nashikcell 4870011135

distance 0.225

#17 · Nashikcell 4870011008

distance 0.227

#18 · Nashikcell 4870011130

distance 0.229

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":487,"cluster_id":4870010751}}}'

Machine-readable JSON twin →Full dossier →

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.