{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:VE6KB5JQI2XLLHIHB3MKJKX45D","short_pith_number":"pith:VE6KB5JQ","schema_version":"1.0","canonical_sha256":"a93ca0f53046aeb59d070ed8a4aafce8f63ae74beda056c4ae66c63edbbfdedb","source":{"kind":"arxiv","id":"2606.29721","version":1},"attestation_state":"computed","paper":{"title":"Redefining Maritime Anomaly Detection via Equation-Grounded Synthetic Anomalies","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Dohun Lee, Hyunwoo Park, Jaeeun Seo, Jeehong Kim, Sungho Bae, Wonhee Lee, Youngseok Hwang","submitted_at":"2026-06-29T02:56:46Z","abstract_excerpt":"Maritime anomaly detection is essential for ensuring maritime safety, security, and efficient traffic management at sea, with Automatic Identification System (AIS) data serving as a primary data source. Despite its importance, most publicly available AIS datasets lack predefined anomaly labels, forcing prior studies to rely on either distribution-based rarity or domain rule/expert-assisted labeling. These approaches, however, face fundamental limitations: statistical rarity often fails to reflect practically critical events, while expert-based labeling is costly, subjective, and difficult to s"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.29721","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-29T02:56:46Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b27e65f69566d4d258ad4c2d42f301440efb3050488f2a46f8e6aed037e1e986","abstract_canon_sha256":"0043431916c47d8bf19a26d9b8299b0d4a9c1eb8a858aa2926c5e46427228548"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T02:17:32.054141Z","signature_b64":"r+NrKE4DUwBSwEJRoRN5U8wyC5XFr7/qdILYqHnjhqtu6CxUGsowjA5Y7C1M7mzEwUbxD+NZgpz1RMjDBf52Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a93ca0f53046aeb59d070ed8a4aafce8f63ae74beda056c4ae66c63edbbfdedb","last_reissued_at":"2026-06-30T02:17:32.053711Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T02:17:32.053711Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Redefining Maritime Anomaly Detection via Equation-Grounded Synthetic Anomalies","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Dohun Lee, Hyunwoo Park, Jaeeun Seo, Jeehong Kim, Sungho Bae, Wonhee Lee, Youngseok Hwang","submitted_at":"2026-06-29T02:56:46Z","abstract_excerpt":"Maritime anomaly detection is essential for ensuring maritime safety, security, and efficient traffic management at sea, with Automatic Identification System (AIS) data serving as a primary data source. Despite its importance, most publicly available AIS datasets lack predefined anomaly labels, forcing prior studies to rely on either distribution-based rarity or domain rule/expert-assisted labeling. These approaches, however, face fundamental limitations: statistical rarity often fails to reflect practically critical events, while expert-based labeling is costly, subjective, and difficult to s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.29721","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/2606.29721/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.29721","created_at":"2026-06-30T02:17:32.053774+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.29721v1","created_at":"2026-06-30T02:17:32.053774+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.29721","created_at":"2026-06-30T02:17:32.053774+00:00"},{"alias_kind":"pith_short_12","alias_value":"VE6KB5JQI2XL","created_at":"2026-06-30T02:17:32.053774+00:00"},{"alias_kind":"pith_short_16","alias_value":"VE6KB5JQI2XLLHIH","created_at":"2026-06-30T02:17:32.053774+00:00"},{"alias_kind":"pith_short_8","alias_value":"VE6KB5JQ","created_at":"2026-06-30T02:17:32.053774+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VE6KB5JQI2XLLHIHB3MKJKX45D","json":"https://pith.science/pith/VE6KB5JQI2XLLHIHB3MKJKX45D.json","graph_json":"https://pith.science/api/pith-number/VE6KB5JQI2XLLHIHB3MKJKX45D/graph.json","events_json":"https://pith.science/api/pith-number/VE6KB5JQI2XLLHIHB3MKJKX45D/events.json","paper":"https://pith.science/paper/VE6KB5JQ"},"agent_actions":{"view_html":"https://pith.science/pith/VE6KB5JQI2XLLHIHB3MKJKX45D","download_json":"https://pith.science/pith/VE6KB5JQI2XLLHIHB3MKJKX45D.json","view_paper":"https://pith.science/paper/VE6KB5JQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.29721&json=true","fetch_graph":"https://pith.science/api/pith-number/VE6KB5JQI2XLLHIHB3MKJKX45D/graph.json","fetch_events":"https://pith.science/api/pith-number/VE6KB5JQI2XLLHIHB3MKJKX45D/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VE6KB5JQI2XLLHIHB3MKJKX45D/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VE6KB5JQI2XLLHIHB3MKJKX45D/action/storage_attestation","attest_author":"https://pith.science/pith/VE6KB5JQI2XLLHIHB3MKJKX45D/action/author_attestation","sign_citation":"https://pith.science/pith/VE6KB5JQI2XLLHIHB3MKJKX45D/action/citation_signature","submit_replication":"https://pith.science/pith/VE6KB5JQI2XLLHIHB3MKJKX45D/action/replication_record"}},"created_at":"2026-06-30T02:17:32.053774+00:00","updated_at":"2026-06-30T02:17:32.053774+00:00"}