{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:N5CKWVOSTVQAAQDLLHR672DVI7","short_pith_number":"pith:N5CKWVOS","schema_version":"1.0","canonical_sha256":"6f44ab55d29d6000406b59e3efe87547ce2e82b6b485b5cc96347b1a912e6beb","source":{"kind":"arxiv","id":"1806.04497","version":1},"attestation_state":"computed","paper":{"title":"A Virtual Environment with Multi-Robot Navigation, Analytics, and Decision Support for Critical Incident Investigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CY","authors_text":"Brett Drury, David L. Smyth, Frank G. Glavin, Ihsan Ullah, James Fennell, Michael G. Madden, Nazli B. Karimi, Sai Abinesh","submitted_at":"2018-06-12T13:26:56Z","abstract_excerpt":"Accidents and attacks that involve chemical, biological, radiological/nuclear or explosive (CBRNE) substances are rare, but can be of high consequence. Since the investigation of such events is not anybody's routine work, a range of AI techniques can reduce investigators' cognitive load and support decision-making, including: planning the assessment of the scene; ongoing evaluation and updating of risks; control of autonomous vehicles for collecting images and sensor data; reviewing images/videos for items of interest; identification of anomalies; and retrieval of relevant documentation. Becau"},"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":"1806.04497","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2018-06-12T13:26:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1c3a6decd5bb7df51509afd791b6e551321c60c5664aad301b9028a6f716f2a1","abstract_canon_sha256":"112cb3095a40801b134bc3ba56c6d06823689be0e3a05e6fda83d535de437a91"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:13:35.353454Z","signature_b64":"dXCcfzCyjXswajSMSyfwoP1cFxLT7uCljloQX5GHs0BzRGd89uRR9GaUPNSic6KRCwxqGouxMuly7KwTHriBAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6f44ab55d29d6000406b59e3efe87547ce2e82b6b485b5cc96347b1a912e6beb","last_reissued_at":"2026-05-18T00:13:35.352710Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:13:35.352710Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Virtual Environment with Multi-Robot Navigation, Analytics, and Decision Support for Critical Incident Investigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CY","authors_text":"Brett Drury, David L. Smyth, Frank G. Glavin, Ihsan Ullah, James Fennell, Michael G. Madden, Nazli B. Karimi, Sai Abinesh","submitted_at":"2018-06-12T13:26:56Z","abstract_excerpt":"Accidents and attacks that involve chemical, biological, radiological/nuclear or explosive (CBRNE) substances are rare, but can be of high consequence. Since the investigation of such events is not anybody's routine work, a range of AI techniques can reduce investigators' cognitive load and support decision-making, including: planning the assessment of the scene; ongoing evaluation and updating of risks; control of autonomous vehicles for collecting images and sensor data; reviewing images/videos for items of interest; identification of anomalies; and retrieval of relevant documentation. Becau"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.04497","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1806.04497","created_at":"2026-05-18T00:13:35.352811+00:00"},{"alias_kind":"arxiv_version","alias_value":"1806.04497v1","created_at":"2026-05-18T00:13:35.352811+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.04497","created_at":"2026-05-18T00:13:35.352811+00:00"},{"alias_kind":"pith_short_12","alias_value":"N5CKWVOSTVQA","created_at":"2026-05-18T12:32:40.477152+00:00"},{"alias_kind":"pith_short_16","alias_value":"N5CKWVOSTVQAAQDL","created_at":"2026-05-18T12:32:40.477152+00:00"},{"alias_kind":"pith_short_8","alias_value":"N5CKWVOS","created_at":"2026-05-18T12:32:40.477152+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/N5CKWVOSTVQAAQDLLHR672DVI7","json":"https://pith.science/pith/N5CKWVOSTVQAAQDLLHR672DVI7.json","graph_json":"https://pith.science/api/pith-number/N5CKWVOSTVQAAQDLLHR672DVI7/graph.json","events_json":"https://pith.science/api/pith-number/N5CKWVOSTVQAAQDLLHR672DVI7/events.json","paper":"https://pith.science/paper/N5CKWVOS"},"agent_actions":{"view_html":"https://pith.science/pith/N5CKWVOSTVQAAQDLLHR672DVI7","download_json":"https://pith.science/pith/N5CKWVOSTVQAAQDLLHR672DVI7.json","view_paper":"https://pith.science/paper/N5CKWVOS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1806.04497&json=true","fetch_graph":"https://pith.science/api/pith-number/N5CKWVOSTVQAAQDLLHR672DVI7/graph.json","fetch_events":"https://pith.science/api/pith-number/N5CKWVOSTVQAAQDLLHR672DVI7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/N5CKWVOSTVQAAQDLLHR672DVI7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/N5CKWVOSTVQAAQDLLHR672DVI7/action/storage_attestation","attest_author":"https://pith.science/pith/N5CKWVOSTVQAAQDLLHR672DVI7/action/author_attestation","sign_citation":"https://pith.science/pith/N5CKWVOSTVQAAQDLLHR672DVI7/action/citation_signature","submit_replication":"https://pith.science/pith/N5CKWVOSTVQAAQDLLHR672DVI7/action/replication_record"}},"created_at":"2026-05-18T00:13:35.352811+00:00","updated_at":"2026-05-18T00:13:35.352811+00:00"}