{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:XRYWKAPIGD6QU4U7TZPJSVGKFB","short_pith_number":"pith:XRYWKAPI","canonical_record":{"source":{"id":"2605.27884","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-27T03:07:53Z","cross_cats_sorted":[],"title_canon_sha256":"edd6241b00ddfcd8f54b6252dc765f8cec4fa82cf42611d73103959812bbf669","abstract_canon_sha256":"258d7cad557294805fe8e1354624c61448a7c03936de541b1139d20229a49448"},"schema_version":"1.0"},"canonical_sha256":"bc716501e830fd0a729f9e5e9954ca286662054201aab20043f22fc10bafe7a0","source":{"kind":"arxiv","id":"2605.27884","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.27884","created_at":"2026-05-28T01:04:51Z"},{"alias_kind":"arxiv_version","alias_value":"2605.27884v1","created_at":"2026-05-28T01:04:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.27884","created_at":"2026-05-28T01:04:51Z"},{"alias_kind":"pith_short_12","alias_value":"XRYWKAPIGD6Q","created_at":"2026-05-28T01:04:51Z"},{"alias_kind":"pith_short_16","alias_value":"XRYWKAPIGD6QU4U7","created_at":"2026-05-28T01:04:51Z"},{"alias_kind":"pith_short_8","alias_value":"XRYWKAPI","created_at":"2026-05-28T01:04:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:XRYWKAPIGD6QU4U7TZPJSVGKFB","target":"record","payload":{"canonical_record":{"source":{"id":"2605.27884","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-27T03:07:53Z","cross_cats_sorted":[],"title_canon_sha256":"edd6241b00ddfcd8f54b6252dc765f8cec4fa82cf42611d73103959812bbf669","abstract_canon_sha256":"258d7cad557294805fe8e1354624c61448a7c03936de541b1139d20229a49448"},"schema_version":"1.0"},"canonical_sha256":"bc716501e830fd0a729f9e5e9954ca286662054201aab20043f22fc10bafe7a0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-28T01:04:51.219052Z","signature_b64":"0st6RXQCukPXLU/tFEeJ6XZKq5Lq8DK8HUzhLgZPZwtGnfts1/0HrJ5h1NJzjEKEWKlBPDn02oCzwzQiYCFIAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc716501e830fd0a729f9e5e9954ca286662054201aab20043f22fc10bafe7a0","last_reissued_at":"2026-05-28T01:04:51.218687Z","signature_status":"signed_v1","first_computed_at":"2026-05-28T01:04:51.218687Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.27884","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":"2026-05-28T01:04:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LJPMecXYE+3TJ+eam0tSptA29AU/hSwo616k9hNICRvy26Jnm62DyeDacl0mTm53H1+bOwtIG6eyG1tpmtz4Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T13:24:16.869475Z"},"content_sha256":"4ec68735acbf670b870458db839ddadbec1944806ec1e2fafda211211d7ab268","schema_version":"1.0","event_id":"sha256:4ec68735acbf670b870458db839ddadbec1944806ec1e2fafda211211d7ab268"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:XRYWKAPIGD6QU4U7TZPJSVGKFB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Road-Conditioned Traffic Movie Prediction Network with Spatiotemporal and Structure-Consistent Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Armstrong Aboah, Blessing Agyei Kyem, Joshua Kofi Asamoah","submitted_at":"2026-05-27T03:07:53Z","abstract_excerpt":"City-wide traffic forecasting is important for congestion management, route guidance, and intelligent transportation systems, but accurate prediction remains challenging when future traffic must be generated as spatial maps over an entire urban network. Existing traffic movie prediction methods have improved frame-level accuracy, yet many still treat forecasting mainly as image reconstruction. This can produce traffic maps that are numerically close to the ground truth but weakly constrained by road layout, connectivity, travel direction, and congestion propagation, especially in cross-city se"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.27884","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.27884/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":"2026-05-28T01:04:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RrGT2u42uPPu3gkRNUERwph1Vjmr1rJe953Bg6iIHFVs7mPtveK5dep9KD21Tv2ZdiYWGDYSFTVPT85qQXUsCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T13:24:16.869838Z"},"content_sha256":"9680905454674e55f984d3cef1fab3941d0e825e8bf84e5542d3c23ace0b6130","schema_version":"1.0","event_id":"sha256:9680905454674e55f984d3cef1fab3941d0e825e8bf84e5542d3c23ace0b6130"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XRYWKAPIGD6QU4U7TZPJSVGKFB/bundle.json","state_url":"https://pith.science/pith/XRYWKAPIGD6QU4U7TZPJSVGKFB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XRYWKAPIGD6QU4U7TZPJSVGKFB/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":"2026-07-09T13:24:16Z","links":{"resolver":"https://pith.science/pith/XRYWKAPIGD6QU4U7TZPJSVGKFB","bundle":"https://pith.science/pith/XRYWKAPIGD6QU4U7TZPJSVGKFB/bundle.json","state":"https://pith.science/pith/XRYWKAPIGD6QU4U7TZPJSVGKFB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XRYWKAPIGD6QU4U7TZPJSVGKFB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:XRYWKAPIGD6QU4U7TZPJSVGKFB","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":"258d7cad557294805fe8e1354624c61448a7c03936de541b1139d20229a49448","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-27T03:07:53Z","title_canon_sha256":"edd6241b00ddfcd8f54b6252dc765f8cec4fa82cf42611d73103959812bbf669"},"schema_version":"1.0","source":{"id":"2605.27884","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.27884","created_at":"2026-05-28T01:04:51Z"},{"alias_kind":"arxiv_version","alias_value":"2605.27884v1","created_at":"2026-05-28T01:04:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.27884","created_at":"2026-05-28T01:04:51Z"},{"alias_kind":"pith_short_12","alias_value":"XRYWKAPIGD6Q","created_at":"2026-05-28T01:04:51Z"},{"alias_kind":"pith_short_16","alias_value":"XRYWKAPIGD6QU4U7","created_at":"2026-05-28T01:04:51Z"},{"alias_kind":"pith_short_8","alias_value":"XRYWKAPI","created_at":"2026-05-28T01:04:51Z"}],"graph_snapshots":[{"event_id":"sha256:9680905454674e55f984d3cef1fab3941d0e825e8bf84e5542d3c23ace0b6130","target":"graph","created_at":"2026-05-28T01:04:51Z","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/2605.27884/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"City-wide traffic forecasting is important for congestion management, route guidance, and intelligent transportation systems, but accurate prediction remains challenging when future traffic must be generated as spatial maps over an entire urban network. Existing traffic movie prediction methods have improved frame-level accuracy, yet many still treat forecasting mainly as image reconstruction. This can produce traffic maps that are numerically close to the ground truth but weakly constrained by road layout, connectivity, travel direction, and congestion propagation, especially in cross-city se","authors_text":"Armstrong Aboah, Blessing Agyei Kyem, Joshua Kofi Asamoah","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-27T03:07:53Z","title":"A Road-Conditioned Traffic Movie Prediction Network with Spatiotemporal and Structure-Consistent Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.27884","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":"sha256:4ec68735acbf670b870458db839ddadbec1944806ec1e2fafda211211d7ab268","target":"record","created_at":"2026-05-28T01:04:51Z","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":"258d7cad557294805fe8e1354624c61448a7c03936de541b1139d20229a49448","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-27T03:07:53Z","title_canon_sha256":"edd6241b00ddfcd8f54b6252dc765f8cec4fa82cf42611d73103959812bbf669"},"schema_version":"1.0","source":{"id":"2605.27884","kind":"arxiv","version":1}},"canonical_sha256":"bc716501e830fd0a729f9e5e9954ca286662054201aab20043f22fc10bafe7a0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bc716501e830fd0a729f9e5e9954ca286662054201aab20043f22fc10bafe7a0","first_computed_at":"2026-05-28T01:04:51.218687Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-28T01:04:51.218687Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0st6RXQCukPXLU/tFEeJ6XZKq5Lq8DK8HUzhLgZPZwtGnfts1/0HrJ5h1NJzjEKEWKlBPDn02oCzwzQiYCFIAg==","signature_status":"signed_v1","signed_at":"2026-05-28T01:04:51.219052Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.27884","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4ec68735acbf670b870458db839ddadbec1944806ec1e2fafda211211d7ab268","sha256:9680905454674e55f984d3cef1fab3941d0e825e8bf84e5542d3c23ace0b6130"],"state_sha256":"58e70a50cacd7e7af0c2d9fdf0550a9efcae13c2b92c9c2f059a604a500facb4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1RpiZSkYnvj6C+FPGtNeW+WRSbE1wAaiMxIggoFaIn/x+RmjXdNAjF9Kcs7pexvD0h+/o0onoazLJzAKOwPyBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T13:24:16.871920Z","bundle_sha256":"35410119de27fcb39ea3eae8c7f7c548cf77310417191fb5261a75b4096e61f3"}}