{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:FSBARRUXWTZ2KTGTN2HH5C7CAX","short_pith_number":"pith:FSBARRUX","canonical_record":{"source":{"id":"1903.09714","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2019-03-22T21:43:45Z","cross_cats_sorted":[],"title_canon_sha256":"b28bbf82c66a8069a6eb43a8d4741f3e4ad029ef6203519b9da66ce9dd68b562","abstract_canon_sha256":"f064635ace5027b65f8698ad5fd6aac010adb02333ef4cb9d804dcc44fddd789"},"schema_version":"1.0"},"canonical_sha256":"2c8208c697b4f3a54cd36e8e7e8be205c8f9e3918301a4edd87567314297314d","source":{"kind":"arxiv","id":"1903.09714","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.09714","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"arxiv_version","alias_value":"1903.09714v1","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.09714","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"pith_short_12","alias_value":"FSBARRUXWTZ2","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"FSBARRUXWTZ2KTGT","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"FSBARRUX","created_at":"2026-05-18T12:33:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:FSBARRUXWTZ2KTGTN2HH5C7CAX","target":"record","payload":{"canonical_record":{"source":{"id":"1903.09714","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2019-03-22T21:43:45Z","cross_cats_sorted":[],"title_canon_sha256":"b28bbf82c66a8069a6eb43a8d4741f3e4ad029ef6203519b9da66ce9dd68b562","abstract_canon_sha256":"f064635ace5027b65f8698ad5fd6aac010adb02333ef4cb9d804dcc44fddd789"},"schema_version":"1.0"},"canonical_sha256":"2c8208c697b4f3a54cd36e8e7e8be205c8f9e3918301a4edd87567314297314d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:50:35.696501Z","signature_b64":"/kYnhZeJ9J1i+usodvTev5JnVhtxebFGXQ+tPPac/rWAhnwIlDiOsiUMxMOzBwTj/YAYcjTfhWHcpekhdxgICQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2c8208c697b4f3a54cd36e8e7e8be205c8f9e3918301a4edd87567314297314d","last_reissued_at":"2026-05-17T23:50:35.695787Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:50:35.695787Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.09714","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":"2026-05-17T23:50:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"18AqlkkCah8mF4jjcfAene2qZ1dF8Z2Sd1QCQjzZkY59ZkOWaxQP/3twnOjTgfZaIvjI6ETmZfTX5cO+OFzYAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T15:28:03.803627Z"},"content_sha256":"17c533b38c2cdb7b95f85eb94ae53ab32e14930f86a425c51c982ba121cb1690","schema_version":"1.0","event_id":"sha256:17c533b38c2cdb7b95f85eb94ae53ab32e14930f86a425c51c982ba121cb1690"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:FSBARRUXWTZ2KTGTN2HH5C7CAX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Graph Temporal Logic Inference for Classification and Identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LO","authors_text":"A. Agung Julius, Alexander J Nettekoven, Ufuk Topcu, Zhe Xu","submitted_at":"2019-03-22T21:43:45Z","abstract_excerpt":"Inferring spatial-temporal properties from data is important for many complex systems, such as additive manufacturing systems, swarm robotic systems and biological networks. Such systems can often be modeled as a labeled graph where labels on the nodes and edges represent relevant measurements such as temperatures and distances. We introduce graph temporal logic (GTL) which can express properties such as \"whenever a node's label is above 10, for the next 3 time units there are always at least two neighboring nodes with an edge label of at most 2 where the node labels are above 5\". This paper i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.09714","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":"2026-05-17T23:50:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sWAp9fiEmdRz11wJDAS/MMCQITdBoKNXIPVTmknPOyCb5Y/4kQidU0DWbxSH26CxGlKSgvWEGtyaiC24JsTrDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T15:28:03.804194Z"},"content_sha256":"4066970584f4865f07719719c09491b27777bb65a30bce48d7e2181ac408466d","schema_version":"1.0","event_id":"sha256:4066970584f4865f07719719c09491b27777bb65a30bce48d7e2181ac408466d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FSBARRUXWTZ2KTGTN2HH5C7CAX/bundle.json","state_url":"https://pith.science/pith/FSBARRUXWTZ2KTGTN2HH5C7CAX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FSBARRUXWTZ2KTGTN2HH5C7CAX/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":"2026-05-29T15:28:03Z","links":{"resolver":"https://pith.science/pith/FSBARRUXWTZ2KTGTN2HH5C7CAX","bundle":"https://pith.science/pith/FSBARRUXWTZ2KTGTN2HH5C7CAX/bundle.json","state":"https://pith.science/pith/FSBARRUXWTZ2KTGTN2HH5C7CAX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FSBARRUXWTZ2KTGTN2HH5C7CAX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:FSBARRUXWTZ2KTGTN2HH5C7CAX","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":"f064635ace5027b65f8698ad5fd6aac010adb02333ef4cb9d804dcc44fddd789","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2019-03-22T21:43:45Z","title_canon_sha256":"b28bbf82c66a8069a6eb43a8d4741f3e4ad029ef6203519b9da66ce9dd68b562"},"schema_version":"1.0","source":{"id":"1903.09714","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.09714","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"arxiv_version","alias_value":"1903.09714v1","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.09714","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"pith_short_12","alias_value":"FSBARRUXWTZ2","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"FSBARRUXWTZ2KTGT","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"FSBARRUX","created_at":"2026-05-18T12:33:15Z"}],"graph_snapshots":[{"event_id":"sha256:4066970584f4865f07719719c09491b27777bb65a30bce48d7e2181ac408466d","target":"graph","created_at":"2026-05-17T23:50:35Z","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":"Inferring spatial-temporal properties from data is important for many complex systems, such as additive manufacturing systems, swarm robotic systems and biological networks. Such systems can often be modeled as a labeled graph where labels on the nodes and edges represent relevant measurements such as temperatures and distances. We introduce graph temporal logic (GTL) which can express properties such as \"whenever a node's label is above 10, for the next 3 time units there are always at least two neighboring nodes with an edge label of at most 2 where the node labels are above 5\". This paper i","authors_text":"A. Agung Julius, Alexander J Nettekoven, Ufuk Topcu, Zhe Xu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2019-03-22T21:43:45Z","title":"Graph Temporal Logic Inference for Classification and Identification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.09714","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":"sha256:17c533b38c2cdb7b95f85eb94ae53ab32e14930f86a425c51c982ba121cb1690","target":"record","created_at":"2026-05-17T23:50:35Z","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":"f064635ace5027b65f8698ad5fd6aac010adb02333ef4cb9d804dcc44fddd789","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2019-03-22T21:43:45Z","title_canon_sha256":"b28bbf82c66a8069a6eb43a8d4741f3e4ad029ef6203519b9da66ce9dd68b562"},"schema_version":"1.0","source":{"id":"1903.09714","kind":"arxiv","version":1}},"canonical_sha256":"2c8208c697b4f3a54cd36e8e7e8be205c8f9e3918301a4edd87567314297314d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2c8208c697b4f3a54cd36e8e7e8be205c8f9e3918301a4edd87567314297314d","first_computed_at":"2026-05-17T23:50:35.695787Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:50:35.695787Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/kYnhZeJ9J1i+usodvTev5JnVhtxebFGXQ+tPPac/rWAhnwIlDiOsiUMxMOzBwTj/YAYcjTfhWHcpekhdxgICQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:50:35.696501Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.09714","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:17c533b38c2cdb7b95f85eb94ae53ab32e14930f86a425c51c982ba121cb1690","sha256:4066970584f4865f07719719c09491b27777bb65a30bce48d7e2181ac408466d"],"state_sha256":"d7279e47870d768364cc5043ca2444ef633fef55243957e313e9123afb20eb7e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SOQ0SKciKyWKFN57qgLiZl8nn/JiqzLTbc8wktHjy9g4L+wbOli4x18bQyb/N46vVmNL2J4I82xsWg6l/ISgCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-29T15:28:03.807837Z","bundle_sha256":"c643dd794730e4bac780767c8d6fd3f65902b1a07dd3a801e0ebd5438a5c0411"}}