{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:JLFJOKDO3DJQZZSYFCNCR6HPG5","short_pith_number":"pith:JLFJOKDO","canonical_record":{"source":{"id":"2202.01888","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-02-01T06:04:18Z","cross_cats_sorted":["eess.SP"],"title_canon_sha256":"fdf5b29b5ca78adbb339f9e0495d4d196fd7675d4414b0b722ea059df67ea205","abstract_canon_sha256":"ed38d4badf37bd16184b00beaa9c336b8431c3d766102b4b86d7110067b2a99c"},"schema_version":"1.0"},"canonical_sha256":"4aca97286ed8d30ce658289a28f8ef37419e9a4c71c667347be4197118fe0745","source":{"kind":"arxiv","id":"2202.01888","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.01888","created_at":"2026-07-05T06:00:11Z"},{"alias_kind":"arxiv_version","alias_value":"2202.01888v2","created_at":"2026-07-05T06:00:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.01888","created_at":"2026-07-05T06:00:11Z"},{"alias_kind":"pith_short_12","alias_value":"JLFJOKDO3DJQ","created_at":"2026-07-05T06:00:11Z"},{"alias_kind":"pith_short_16","alias_value":"JLFJOKDO3DJQZZSY","created_at":"2026-07-05T06:00:11Z"},{"alias_kind":"pith_short_8","alias_value":"JLFJOKDO","created_at":"2026-07-05T06:00:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:JLFJOKDO3DJQZZSYFCNCR6HPG5","target":"record","payload":{"canonical_record":{"source":{"id":"2202.01888","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-02-01T06:04:18Z","cross_cats_sorted":["eess.SP"],"title_canon_sha256":"fdf5b29b5ca78adbb339f9e0495d4d196fd7675d4414b0b722ea059df67ea205","abstract_canon_sha256":"ed38d4badf37bd16184b00beaa9c336b8431c3d766102b4b86d7110067b2a99c"},"schema_version":"1.0"},"canonical_sha256":"4aca97286ed8d30ce658289a28f8ef37419e9a4c71c667347be4197118fe0745","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:00:11.087171Z","signature_b64":"uQzx5NFF7Pd4Hm+sKxiO3zzUPOfJxXnoANdBzbGIHTWRHECBQzl9z1M3pkgiQ3zl3OiytV3ymHek0cPboKeJBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4aca97286ed8d30ce658289a28f8ef37419e9a4c71c667347be4197118fe0745","last_reissued_at":"2026-07-05T06:00:11.086736Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:00:11.086736Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2202.01888","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:00:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2xYancuhuf0sEFu5uHHx2ExApMJ1XbWCOMLEaG7Vohs4Hsute2kU4+g3jqdE1s3HK5qyDW7NjHiEpvjIvg6nDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T02:40:12.887433Z"},"content_sha256":"d296358269a7539f9fe5ed9d91ff5318a78db180f6ce72115a87ae2cda0e5425","schema_version":"1.0","event_id":"sha256:d296358269a7539f9fe5ed9d91ff5318a78db180f6ce72115a87ae2cda0e5425"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:JLFJOKDO3DJQZZSYFCNCR6HPG5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Hybrid Physics Machine Learning Approach for Macroscopic Traffic State Estimation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["eess.SP"],"primary_cat":"cs.LG","authors_text":"Ding Zhao, Xianfeng Terry Yang, Zhao Zhang","submitted_at":"2022-02-01T06:04:18Z","abstract_excerpt":"Full-field traffic state information (i.e., flow, speed, and density) is critical for the successful operation of Intelligent Transportation Systems (ITS) on freeways. However, incomplete traffic information tends to be directly collected from traffic detectors that are insufficiently installed in most areas, which is a major obstacle to the popularization of ITS. To tackle this issue, this paper introduces an innovative traffic state estimation (TSE) framework that hybrid regression machine learning techniques (e.g., artificial neural network (ANN), random forest (RF), and support vector mach"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.01888","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2202.01888/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T06:00:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7SA+bnNNp+nZx9X4SFcxLLlyYkKfENa8WrZSKX3uOWTX56oj9aPHVmgs21dnt0//9y9Ljo3UJ3akHDDMJZtPBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T02:40:12.887924Z"},"content_sha256":"715c7ae2df14e878a75164052b1f0c26dd366787077f903aec679d3fae5ab201","schema_version":"1.0","event_id":"sha256:715c7ae2df14e878a75164052b1f0c26dd366787077f903aec679d3fae5ab201"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JLFJOKDO3DJQZZSYFCNCR6HPG5/bundle.json","state_url":"https://pith.science/pith/JLFJOKDO3DJQZZSYFCNCR6HPG5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JLFJOKDO3DJQZZSYFCNCR6HPG5/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":"2026-08-17T02:40:12Z","links":{"resolver":"https://pith.science/pith/JLFJOKDO3DJQZZSYFCNCR6HPG5","bundle":"https://pith.science/pith/JLFJOKDO3DJQZZSYFCNCR6HPG5/bundle.json","state":"https://pith.science/pith/JLFJOKDO3DJQZZSYFCNCR6HPG5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JLFJOKDO3DJQZZSYFCNCR6HPG5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:JLFJOKDO3DJQZZSYFCNCR6HPG5","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":"ed38d4badf37bd16184b00beaa9c336b8431c3d766102b4b86d7110067b2a99c","cross_cats_sorted":["eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-02-01T06:04:18Z","title_canon_sha256":"fdf5b29b5ca78adbb339f9e0495d4d196fd7675d4414b0b722ea059df67ea205"},"schema_version":"1.0","source":{"id":"2202.01888","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.01888","created_at":"2026-07-05T06:00:11Z"},{"alias_kind":"arxiv_version","alias_value":"2202.01888v2","created_at":"2026-07-05T06:00:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.01888","created_at":"2026-07-05T06:00:11Z"},{"alias_kind":"pith_short_12","alias_value":"JLFJOKDO3DJQ","created_at":"2026-07-05T06:00:11Z"},{"alias_kind":"pith_short_16","alias_value":"JLFJOKDO3DJQZZSY","created_at":"2026-07-05T06:00:11Z"},{"alias_kind":"pith_short_8","alias_value":"JLFJOKDO","created_at":"2026-07-05T06:00:11Z"}],"graph_snapshots":[{"event_id":"sha256:715c7ae2df14e878a75164052b1f0c26dd366787077f903aec679d3fae5ab201","target":"graph","created_at":"2026-07-05T06:00:11Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2202.01888/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Full-field traffic state information (i.e., flow, speed, and density) is critical for the successful operation of Intelligent Transportation Systems (ITS) on freeways. However, incomplete traffic information tends to be directly collected from traffic detectors that are insufficiently installed in most areas, which is a major obstacle to the popularization of ITS. To tackle this issue, this paper introduces an innovative traffic state estimation (TSE) framework that hybrid regression machine learning techniques (e.g., artificial neural network (ANN), random forest (RF), and support vector mach","authors_text":"Ding Zhao, Xianfeng Terry Yang, Zhao Zhang","cross_cats":["eess.SP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-02-01T06:04:18Z","title":"A Hybrid Physics Machine Learning Approach for Macroscopic Traffic State Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.01888","kind":"arxiv","version":2},"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:d296358269a7539f9fe5ed9d91ff5318a78db180f6ce72115a87ae2cda0e5425","target":"record","created_at":"2026-07-05T06:00:11Z","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":"ed38d4badf37bd16184b00beaa9c336b8431c3d766102b4b86d7110067b2a99c","cross_cats_sorted":["eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-02-01T06:04:18Z","title_canon_sha256":"fdf5b29b5ca78adbb339f9e0495d4d196fd7675d4414b0b722ea059df67ea205"},"schema_version":"1.0","source":{"id":"2202.01888","kind":"arxiv","version":2}},"canonical_sha256":"4aca97286ed8d30ce658289a28f8ef37419e9a4c71c667347be4197118fe0745","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4aca97286ed8d30ce658289a28f8ef37419e9a4c71c667347be4197118fe0745","first_computed_at":"2026-07-05T06:00:11.086736Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:00:11.086736Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uQzx5NFF7Pd4Hm+sKxiO3zzUPOfJxXnoANdBzbGIHTWRHECBQzl9z1M3pkgiQ3zl3OiytV3ymHek0cPboKeJBA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:00:11.087171Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.01888","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d296358269a7539f9fe5ed9d91ff5318a78db180f6ce72115a87ae2cda0e5425","sha256:715c7ae2df14e878a75164052b1f0c26dd366787077f903aec679d3fae5ab201"],"state_sha256":"fa28e3617564c26a6d24911e3106fd4ef98ccf35d7b0a7d4a2b0c4d32f595b23"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Jgli2NApn5MJo1WUoCi7k88Vwful9WgIL1/BP6+oH/t3I/x6GGKUQFwHxQDNr8ShfC2Dww2vz/D/MbKFpS9uAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T02:40:12.891056Z","bundle_sha256":"ed064aa67bb9869cffe5f160f401763f1270c9ab8582d9303db52c3fb2813ff6"}}