Bhārata Strata · Maharashtra · Thane · morphological twins

Places like cell 4970000518

The MH-36 locality cells most similar to this Thane 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

0.89

GUM mean confidence of the anchor (R24)

Dimensions compared

morphology-v2 feature dimensions

Closest twin distance

0.285

lower = more alike (weighted)

The twins, closest first

#1 · Thanecell 4970001133

distance 0.285

#2 · Thanecell 4970000586

distance 0.356

#3 · Thanecell 4970000576

distance 0.394

#4 · Thanecell 4970000129

distance 0.395

#5 · Thanecell 4970001025

distance 0.401

#6 · Thanecell 4970000128

distance 0.405

#7 · Thanecell 4970000330

distance 0.406

#8 · Thanecell 4970001117

distance 0.422

#9 · Thanecell 4970000445

distance 0.427

#10 · Thanecell 4970000726

distance 0.436

#11 · Thanecell 4970000386

distance 0.451

#12 · Thanecell 4970000163

distance 0.463

#13 · Thanecell 4970001469

distance 0.488

#14 · Thanecell 4970000643

distance 0.489

#15 · Thanecell 4970000574

distance 0.504

#16 · Mumbai Suburbancell 4830000147

distance 0.519 · cross-district

#17 · Thanecell 4970000641

distance 0.523

#18 · Thanecell 4970000789

distance 0.538

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":497,"cluster_id":4970000518}}}'

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.