{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:6HSOCD5MF4FLRDBMDG7CQXLYQK","short_pith_number":"pith:6HSOCD5M","canonical_record":{"source":{"id":"1904.03444","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-04-06T13:34:44Z","cross_cats_sorted":[],"title_canon_sha256":"71ae0613fbc269d372319b296194fb1fece98c000354d0e318df9eb79907e38a","abstract_canon_sha256":"0ab2443db18392499e315db35b577c00e8ef9f098e88a3b88bb171ba238e4ee8"},"schema_version":"1.0"},"canonical_sha256":"f1e4e10fac2f0ab88c2c19be285d78829466c57de6b5c5d481d8638df3e3b6a4","source":{"kind":"arxiv","id":"1904.03444","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.03444","created_at":"2026-05-17T23:49:13Z"},{"alias_kind":"arxiv_version","alias_value":"1904.03444v1","created_at":"2026-05-17T23:49:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.03444","created_at":"2026-05-17T23:49:13Z"},{"alias_kind":"pith_short_12","alias_value":"6HSOCD5MF4FL","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"6HSOCD5MF4FLRDBM","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"6HSOCD5M","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:6HSOCD5MF4FLRDBMDG7CQXLYQK","target":"record","payload":{"canonical_record":{"source":{"id":"1904.03444","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-04-06T13:34:44Z","cross_cats_sorted":[],"title_canon_sha256":"71ae0613fbc269d372319b296194fb1fece98c000354d0e318df9eb79907e38a","abstract_canon_sha256":"0ab2443db18392499e315db35b577c00e8ef9f098e88a3b88bb171ba238e4ee8"},"schema_version":"1.0"},"canonical_sha256":"f1e4e10fac2f0ab88c2c19be285d78829466c57de6b5c5d481d8638df3e3b6a4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:49:13.378372Z","signature_b64":"SO4cJmWpln2cApABX8/Cqxxd+IjI8Rm76Lc0HUXOE2DH8G3tzZ8yXReiZ7Bt7KZ7HTr1C9MuSykLX0ntyO2RDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f1e4e10fac2f0ab88c2c19be285d78829466c57de6b5c5d481d8638df3e3b6a4","last_reissued_at":"2026-05-17T23:49:13.377684Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:49:13.377684Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.03444","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:49:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lGhJ0UnA3QUR3LXk68XyoEttO0JYBua6RobYXiAbl4/yAKx6LeYbi88MPPEIBEzI2Zx8abRaroSbsozDju1nCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T14:53:46.668693Z"},"content_sha256":"d2dc4cf119a0a66f5e469106530066a860aa07136df741c509af7752946876cf","schema_version":"1.0","event_id":"sha256:d2dc4cf119a0a66f5e469106530066a860aa07136df741c509af7752946876cf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:6HSOCD5MF4FLRDBMDG7CQXLYQK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bus Travel Time Prediction: A Lognormal Auto-Regressive (AR) Modeling Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Avinash Achar, B. Anil Kumar, B. Dhivyabharathi, Lelitha Vanajakshi","submitted_at":"2019-04-06T13:34:44Z","abstract_excerpt":"Providing real time information about the arrival time of the transit buses has become inevitable in urban areas to make the system more user-friendly and advantageous over various other transportation modes. However, accurate prediction of arrival time of buses is still a challenging problem in dynamically varying traffic conditions especially under heterogeneous traffic condition without lane discipline. One broad approach researchers have adopted over the years is to segment the entire bus route into segments and work with these segment travel times as the data input (from GPS traces) for p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.03444","kind":"arxiv","version":1},"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":"2026-05-17T23:49:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xh3CVoFIXwTi3p9X2lxq2DN9CvP8p/kmABCcU73BhhdLZzXfKHXgL6NHsc91OoiBPeKhQUSwopP6BolK1Y/EAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T14:53:46.669033Z"},"content_sha256":"a3dbbae2cc6363d50933274fb9a864eb70d0593428dafee0615a9d118049c503","schema_version":"1.0","event_id":"sha256:a3dbbae2cc6363d50933274fb9a864eb70d0593428dafee0615a9d118049c503"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6HSOCD5MF4FLRDBMDG7CQXLYQK/bundle.json","state_url":"https://pith.science/pith/6HSOCD5MF4FLRDBMDG7CQXLYQK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6HSOCD5MF4FLRDBMDG7CQXLYQK/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":"2026-06-30T14:53:46Z","links":{"resolver":"https://pith.science/pith/6HSOCD5MF4FLRDBMDG7CQXLYQK","bundle":"https://pith.science/pith/6HSOCD5MF4FLRDBMDG7CQXLYQK/bundle.json","state":"https://pith.science/pith/6HSOCD5MF4FLRDBMDG7CQXLYQK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6HSOCD5MF4FLRDBMDG7CQXLYQK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:6HSOCD5MF4FLRDBMDG7CQXLYQK","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":"0ab2443db18392499e315db35b577c00e8ef9f098e88a3b88bb171ba238e4ee8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-04-06T13:34:44Z","title_canon_sha256":"71ae0613fbc269d372319b296194fb1fece98c000354d0e318df9eb79907e38a"},"schema_version":"1.0","source":{"id":"1904.03444","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.03444","created_at":"2026-05-17T23:49:13Z"},{"alias_kind":"arxiv_version","alias_value":"1904.03444v1","created_at":"2026-05-17T23:49:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.03444","created_at":"2026-05-17T23:49:13Z"},{"alias_kind":"pith_short_12","alias_value":"6HSOCD5MF4FL","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"6HSOCD5MF4FLRDBM","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"6HSOCD5M","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:a3dbbae2cc6363d50933274fb9a864eb70d0593428dafee0615a9d118049c503","target":"graph","created_at":"2026-05-17T23:49:13Z","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":"Providing real time information about the arrival time of the transit buses has become inevitable in urban areas to make the system more user-friendly and advantageous over various other transportation modes. However, accurate prediction of arrival time of buses is still a challenging problem in dynamically varying traffic conditions especially under heterogeneous traffic condition without lane discipline. One broad approach researchers have adopted over the years is to segment the entire bus route into segments and work with these segment travel times as the data input (from GPS traces) for p","authors_text":"Avinash Achar, B. Anil Kumar, B. Dhivyabharathi, Lelitha Vanajakshi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-04-06T13:34:44Z","title":"Bus Travel Time Prediction: A Lognormal Auto-Regressive (AR) Modeling Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.03444","kind":"arxiv","version":1},"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:d2dc4cf119a0a66f5e469106530066a860aa07136df741c509af7752946876cf","target":"record","created_at":"2026-05-17T23:49:13Z","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":"0ab2443db18392499e315db35b577c00e8ef9f098e88a3b88bb171ba238e4ee8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-04-06T13:34:44Z","title_canon_sha256":"71ae0613fbc269d372319b296194fb1fece98c000354d0e318df9eb79907e38a"},"schema_version":"1.0","source":{"id":"1904.03444","kind":"arxiv","version":1}},"canonical_sha256":"f1e4e10fac2f0ab88c2c19be285d78829466c57de6b5c5d481d8638df3e3b6a4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f1e4e10fac2f0ab88c2c19be285d78829466c57de6b5c5d481d8638df3e3b6a4","first_computed_at":"2026-05-17T23:49:13.377684Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:49:13.377684Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SO4cJmWpln2cApABX8/Cqxxd+IjI8Rm76Lc0HUXOE2DH8G3tzZ8yXReiZ7Bt7KZ7HTr1C9MuSykLX0ntyO2RDw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:49:13.378372Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.03444","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d2dc4cf119a0a66f5e469106530066a860aa07136df741c509af7752946876cf","sha256:a3dbbae2cc6363d50933274fb9a864eb70d0593428dafee0615a9d118049c503"],"state_sha256":"29020feb7c93a617ce29aac677d4846362c84b100c80f1d8d7a6aa3c93f7ef50"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YmEMTydpx7mRW9VJiBDfIJNC0m+KruJPVhh8Xn0nnwji81wTOwovQUPp9lKcB1tHH9AmIIOpmq9zbttRmeImCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T14:53:46.670882Z","bundle_sha256":"2f550cb19e610ea2688ec339a6aaa680073e165e4d9ec1bd9fe8c6ea13595307"}}