{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:I2UG6SRFG7XV76PSBXRDCGJ3NP","short_pith_number":"pith:I2UG6SRF","canonical_record":{"source":{"id":"1608.00126","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2016-07-30T14:14:52Z","cross_cats_sorted":[],"title_canon_sha256":"b80f3048474087b69f56e2af7b98be7aff95efa5e19cef8f9f4d164abd078349","abstract_canon_sha256":"857a998f78edefb5fc732fc67b84d45a83ec5589d6412eac1229c2fe56d2c325"},"schema_version":"1.0"},"canonical_sha256":"46a86f4a2537ef5ff9f20de231193b6bfac5594e1997ff82d7355af8c29bc6b2","source":{"kind":"arxiv","id":"1608.00126","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1608.00126","created_at":"2026-05-18T00:18:41Z"},{"alias_kind":"arxiv_version","alias_value":"1608.00126v3","created_at":"2026-05-18T00:18:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.00126","created_at":"2026-05-18T00:18:41Z"},{"alias_kind":"pith_short_12","alias_value":"I2UG6SRFG7XV","created_at":"2026-05-18T12:30:22Z"},{"alias_kind":"pith_short_16","alias_value":"I2UG6SRFG7XV76PS","created_at":"2026-05-18T12:30:22Z"},{"alias_kind":"pith_short_8","alias_value":"I2UG6SRF","created_at":"2026-05-18T12:30:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:I2UG6SRFG7XV76PSBXRDCGJ3NP","target":"record","payload":{"canonical_record":{"source":{"id":"1608.00126","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2016-07-30T14:14:52Z","cross_cats_sorted":[],"title_canon_sha256":"b80f3048474087b69f56e2af7b98be7aff95efa5e19cef8f9f4d164abd078349","abstract_canon_sha256":"857a998f78edefb5fc732fc67b84d45a83ec5589d6412eac1229c2fe56d2c325"},"schema_version":"1.0"},"canonical_sha256":"46a86f4a2537ef5ff9f20de231193b6bfac5594e1997ff82d7355af8c29bc6b2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:18:41.703432Z","signature_b64":"wC3EpOl19xfK7IlHWVoqZOzrFi0RPS3iZdIl/J2IcXYjit6ArrmFZHn36hRSrnqUSgdsBppmSs7kdCtOK4ycBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"46a86f4a2537ef5ff9f20de231193b6bfac5594e1997ff82d7355af8c29bc6b2","last_reissued_at":"2026-05-18T00:18:41.702954Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:18:41.702954Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1608.00126","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:18:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RG4LTfx/XGaeEclDFimiOwOtHgQ3o76vN5IZHBjf/CjfqYkiNFliSclit1sqCKMcm87eAV/mafWAoiHunVOVCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T16:18:23.900549Z"},"content_sha256":"8662822a2349d00609176aa4b6653ca6dec0d4a8d6c19c2648c52e56c34d95ec","schema_version":"1.0","event_id":"sha256:8662822a2349d00609176aa4b6653ca6dec0d4a8d6c19c2648c52e56c34d95ec"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:I2UG6SRFG7XV76PSBXRDCGJ3NP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sensitivity analysis of the LWR model for traffic forecast on large networks using Wasserstein distance","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"Elisa Iacomini, Emiliano Cristiani, Maya Briani","submitted_at":"2016-07-30T14:14:52Z","abstract_excerpt":"In this paper we investigate the sensitivity of the LWR model on network to its parameters and to the network itself. The quantification of sensitivity is obtained by measuring the Wasserstein distance between two LWR solutions corresponding to different inputs. To this end, we propose a numerical method to approximate the Wasserstein distance between two density distributions defined on a network. We found a large sensitivity to the traffic distribution at junctions, the network size, and the network topology."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.00126","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:18:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"azrqNHDOGLny0w+gjmhrRwS+UILBx0IUVYh2C3D15SRb/nmtnArVA5IcHj08mR8rCR6koDs6zQJOH5W5wN50BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T16:18:23.901229Z"},"content_sha256":"e9af9bd6878906bfc300014b3cd0e941c14f2c48f19a6d9667a9e1a7affecabe","schema_version":"1.0","event_id":"sha256:e9af9bd6878906bfc300014b3cd0e941c14f2c48f19a6d9667a9e1a7affecabe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/I2UG6SRFG7XV76PSBXRDCGJ3NP/bundle.json","state_url":"https://pith.science/pith/I2UG6SRFG7XV76PSBXRDCGJ3NP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/I2UG6SRFG7XV76PSBXRDCGJ3NP/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-07T16:18:23Z","links":{"resolver":"https://pith.science/pith/I2UG6SRFG7XV76PSBXRDCGJ3NP","bundle":"https://pith.science/pith/I2UG6SRFG7XV76PSBXRDCGJ3NP/bundle.json","state":"https://pith.science/pith/I2UG6SRFG7XV76PSBXRDCGJ3NP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/I2UG6SRFG7XV76PSBXRDCGJ3NP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:I2UG6SRFG7XV76PSBXRDCGJ3NP","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"857a998f78edefb5fc732fc67b84d45a83ec5589d6412eac1229c2fe56d2c325","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2016-07-30T14:14:52Z","title_canon_sha256":"b80f3048474087b69f56e2af7b98be7aff95efa5e19cef8f9f4d164abd078349"},"schema_version":"1.0","source":{"id":"1608.00126","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1608.00126","created_at":"2026-05-18T00:18:41Z"},{"alias_kind":"arxiv_version","alias_value":"1608.00126v3","created_at":"2026-05-18T00:18:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.00126","created_at":"2026-05-18T00:18:41Z"},{"alias_kind":"pith_short_12","alias_value":"I2UG6SRFG7XV","created_at":"2026-05-18T12:30:22Z"},{"alias_kind":"pith_short_16","alias_value":"I2UG6SRFG7XV76PS","created_at":"2026-05-18T12:30:22Z"},{"alias_kind":"pith_short_8","alias_value":"I2UG6SRF","created_at":"2026-05-18T12:30:22Z"}],"graph_snapshots":[{"event_id":"sha256:e9af9bd6878906bfc300014b3cd0e941c14f2c48f19a6d9667a9e1a7affecabe","target":"graph","created_at":"2026-05-18T00:18:41Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"In this paper we investigate the sensitivity of the LWR model on network to its parameters and to the network itself. The quantification of sensitivity is obtained by measuring the Wasserstein distance between two LWR solutions corresponding to different inputs. To this end, we propose a numerical method to approximate the Wasserstein distance between two density distributions defined on a network. We found a large sensitivity to the traffic distribution at junctions, the network size, and the network topology.","authors_text":"Elisa Iacomini, Emiliano Cristiani, Maya Briani","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2016-07-30T14:14:52Z","title":"Sensitivity analysis of the LWR model for traffic forecast on large networks using Wasserstein distance"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.00126","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:8662822a2349d00609176aa4b6653ca6dec0d4a8d6c19c2648c52e56c34d95ec","target":"record","created_at":"2026-05-18T00:18:41Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"857a998f78edefb5fc732fc67b84d45a83ec5589d6412eac1229c2fe56d2c325","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2016-07-30T14:14:52Z","title_canon_sha256":"b80f3048474087b69f56e2af7b98be7aff95efa5e19cef8f9f4d164abd078349"},"schema_version":"1.0","source":{"id":"1608.00126","kind":"arxiv","version":3}},"canonical_sha256":"46a86f4a2537ef5ff9f20de231193b6bfac5594e1997ff82d7355af8c29bc6b2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"46a86f4a2537ef5ff9f20de231193b6bfac5594e1997ff82d7355af8c29bc6b2","first_computed_at":"2026-05-18T00:18:41.702954Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:18:41.702954Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wC3EpOl19xfK7IlHWVoqZOzrFi0RPS3iZdIl/J2IcXYjit6ArrmFZHn36hRSrnqUSgdsBppmSs7kdCtOK4ycBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:18:41.703432Z","signed_message":"canonical_sha256_bytes"},"source_id":"1608.00126","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8662822a2349d00609176aa4b6653ca6dec0d4a8d6c19c2648c52e56c34d95ec","sha256:e9af9bd6878906bfc300014b3cd0e941c14f2c48f19a6d9667a9e1a7affecabe"],"state_sha256":"afc8e3984853d5f0a5504d06f410074b0faf20c25cd5799ce36bd12146d5c528"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u0L0+DTAikFlckbCoWEpKwkNcQfe/TXHyiTa1I3UqGRZ4sj1T8FPtfK+7PTneYBG1qvsjkttrle+lD4HtGj7DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T16:18:23.905338Z","bundle_sha256":"7d12b3d656eb953fb102d036ba629044c76d9e00a7e0953a5d215f8ba6a97152"}}