{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:25MQV3WYBAJBFVFSQAUXGIGYDQ","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":"f80ba60b1c188ecd553dcfbf84d4f383e69f137d568739160f9d9c1fbcfa4685","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.MA","submitted_at":"2025-06-16T03:23:27Z","title_canon_sha256":"7f577908777024605d0aa019b96bd61a7fbc71ab435c81d5c055a8077bb2881b"},"schema_version":"1.0","source":{"id":"2506.13068","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.13068","created_at":"2026-07-05T11:22:42Z"},{"alias_kind":"arxiv_version","alias_value":"2506.13068v2","created_at":"2026-07-05T11:22:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.13068","created_at":"2026-07-05T11:22:42Z"},{"alias_kind":"pith_short_12","alias_value":"25MQV3WYBAJB","created_at":"2026-07-05T11:22:42Z"},{"alias_kind":"pith_short_16","alias_value":"25MQV3WYBAJBFVFS","created_at":"2026-07-05T11:22:42Z"},{"alias_kind":"pith_short_8","alias_value":"25MQV3WY","created_at":"2026-07-05T11:22:42Z"}],"graph_snapshots":[{"event_id":"sha256:8ef010641d3970726ea52108e5eda1eb2c31553e83720215dc0ece5ad8994f7f","target":"graph","created_at":"2026-07-05T11:22:42Z","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/2506.13068/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Optimizing urban freight logistics is critical for developing sustainable, low-carbon cities. Traditional methods often rely on manual coordination of simulation tools, optimization solvers, and expert-driven workflows, limiting their efficiency and scalability. This paper presents an agentic system architecture that leverages the model context protocol (MCP) to orchestrate multi-agent collaboration among scientific tools for autonomous, simulation-informed optimization in urban logistics. The system integrates generative AI agents with domain-specific engines - such as Gurobi for optimization","authors_text":"Haowen Xu, Jose Tupayachi, Olufemi Omitaomu, Sisi Zlatanova, Xueping Li, Yulin Sun","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.MA","submitted_at":"2025-06-16T03:23:27Z","title":"Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.13068","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":"sha256:01de6ca63e92b7ce967a1937bb604eae96ce95c7820fce3945fedf729a344056","target":"record","created_at":"2026-07-05T11:22:42Z","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":"f80ba60b1c188ecd553dcfbf84d4f383e69f137d568739160f9d9c1fbcfa4685","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.MA","submitted_at":"2025-06-16T03:23:27Z","title_canon_sha256":"7f577908777024605d0aa019b96bd61a7fbc71ab435c81d5c055a8077bb2881b"},"schema_version":"1.0","source":{"id":"2506.13068","kind":"arxiv","version":2}},"canonical_sha256":"d7590aeed8081212d4b280297320d81c326c2639f993c12e2abbbb94c7b8c243","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d7590aeed8081212d4b280297320d81c326c2639f993c12e2abbbb94c7b8c243","first_computed_at":"2026-07-05T11:22:42.384877Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:22:42.384877Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N1Sb0jdctuxIumBd1Kh7j8AqsqItMJPDP+rEDIkkDrcuKmQ93bst7H9APiYYz9UMAFb8NAp+aFusfmZRpSoRDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:22:42.385371Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.13068","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:01de6ca63e92b7ce967a1937bb604eae96ce95c7820fce3945fedf729a344056","sha256:8ef010641d3970726ea52108e5eda1eb2c31553e83720215dc0ece5ad8994f7f"],"state_sha256":"fc889d653f63f87fc3c6181110fc11ca14a5e833fa4476b199c36efa71b12157"}