Bhārata Strata · Maharashtra · Sindhudurg · morphological twins
Places like cell 4950002136
The MH-36 locality cells most similar to this Sindhudurg 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
0.9
GUM mean confidence of the anchor (R24)
Dimensions compared
44
morphology-v2 feature dimensions
Closest twin distance
0.078
lower = more alike (weighted)
The twins, closest first
#1 · Sindhudurgcell 4950002096
distance 0.078
#2 · Sindhudurgcell 4950001997
distance 0.079
#3 · Sindhudurgcell 4950002000
distance 0.104
#4 · Sindhudurgcell 4950001945
distance 0.105
#5 · Sindhudurgcell 4950002100
distance 0.116
#6 · Sindhudurgcell 4950002137
distance 0.128
#7 · Sindhudurgcell 4950001998
distance 0.14
#8 · Sindhudurgcell 4950001943
distance 0.167
#9 · Sindhudurgcell 4950001892
distance 0.198
#10 · Sindhudurgcell 4950001944
distance 0.203
#11 · Sindhudurgcell 4950002139
distance 0.215
#12 · Sindhudurgcell 4950001893
distance 0.215
#13 · Sindhudurgcell 4950002140
distance 0.216
#14 · Sindhudurgcell 4950001890
distance 0.218
#15 · Sindhudurgcell 4950002099
distance 0.221
#16 · Ratnagiricell 4920002847
distance 0.227 · cross-district
#17 · Ratnagiricell 4920003125
distance 0.229 · cross-district
#18 · Sindhudurgcell 4950002101
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":495,"cluster_id":4950002136}}}'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.