{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:VOMGLRWXNTHLTXHULXYUAUEEEV","short_pith_number":"pith:VOMGLRWX","canonical_record":{"source":{"id":"1701.07500","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-01-25T21:51:28Z","cross_cats_sorted":[],"title_canon_sha256":"1608da7a0585d857bceccbe01f5f2cca55affd2163662010e416a404776d5042","abstract_canon_sha256":"08ecb6fa6b5be1400e2011d1f13112c06ffe240a0494a095f2029806a6fead9f"},"schema_version":"1.0"},"canonical_sha256":"ab9865c6d76cceb9dcf45df14050842547176955c2f430202fe0d74fd9ce006b","source":{"kind":"arxiv","id":"1701.07500","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1701.07500","created_at":"2026-05-18T00:52:03Z"},{"alias_kind":"arxiv_version","alias_value":"1701.07500v1","created_at":"2026-05-18T00:52:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1701.07500","created_at":"2026-05-18T00:52:03Z"},{"alias_kind":"pith_short_12","alias_value":"VOMGLRWXNTHL","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"VOMGLRWXNTHLTXHU","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"VOMGLRWX","created_at":"2026-05-18T12:31:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:VOMGLRWXNTHLTXHULXYUAUEEEV","target":"record","payload":{"canonical_record":{"source":{"id":"1701.07500","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-01-25T21:51:28Z","cross_cats_sorted":[],"title_canon_sha256":"1608da7a0585d857bceccbe01f5f2cca55affd2163662010e416a404776d5042","abstract_canon_sha256":"08ecb6fa6b5be1400e2011d1f13112c06ffe240a0494a095f2029806a6fead9f"},"schema_version":"1.0"},"canonical_sha256":"ab9865c6d76cceb9dcf45df14050842547176955c2f430202fe0d74fd9ce006b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:52:03.299383Z","signature_b64":"HZpvI0M5ic/miucsJU4298CyNKoWHb96srhoCQ6sDuXLw/nLtZINTiSHIJxXNbdGxxClotWsD0JnW9/aIiGDCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ab9865c6d76cceb9dcf45df14050842547176955c2f430202fe0d74fd9ce006b","last_reissued_at":"2026-05-18T00:52:03.298758Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:52:03.298758Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1701.07500","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":"2026-05-18T00:52:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"extZSi2l/z11fwc/OIHqBzWDhDNKGjWea4o6UNy4jqeAG6fYCM9paVEh8GjJ/Tj7ADKeyY3IeF+PLF2d1A5cDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T17:02:42.146117Z"},"content_sha256":"309b5a8eb0a387d7ccb97011348bee8592f4f52516a4fac144f9a0adada98b84","schema_version":"1.0","event_id":"sha256:309b5a8eb0a387d7ccb97011348bee8592f4f52516a4fac144f9a0adada98b84"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:VOMGLRWXNTHLTXHULXYUAUEEEV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scalable Architecture for Anomaly Detection and Visualization in Power Generating Assets","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Chirag Tailor, Duen Horng Chau, Fang Liu, Liexiao Ding, Michael Phillips, Nagi Gebraeel, Paras Jain, Sam Ford","submitted_at":"2017-01-25T21:51:28Z","abstract_excerpt":"Power-generating assets (e.g., jet engines, gas turbines) are often instrumented with tens to hundreds of sensors for monitoring physical and performance degradation. Anomaly detection algorithms highlight deviations from predetermined benchmarks with the goal of detecting incipient faults. We are developing an integrated system to address three key challenges within analyzing sensor data from power-generating assets: (1) difficulty in ingesting and analyzing data from large numbers of machines; (2) prevalence of false alarms generated by anomaly detection algorithms resulting in unnecessary d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1701.07500","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":"2026-05-18T00:52:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z0IogwBtqqynzxYwQ34PemS3/jGy1guVKkvUcBQo/d7vEmFA3/wamC8L3+ChL+bsGB5z6MaDnV41Br2wLmVgCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T17:02:42.146524Z"},"content_sha256":"df280592dc264cab1926d666383448c205d393af647c72bb2d7a1a5aa7819d76","schema_version":"1.0","event_id":"sha256:df280592dc264cab1926d666383448c205d393af647c72bb2d7a1a5aa7819d76"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VOMGLRWXNTHLTXHULXYUAUEEEV/bundle.json","state_url":"https://pith.science/pith/VOMGLRWXNTHLTXHULXYUAUEEEV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VOMGLRWXNTHLTXHULXYUAUEEEV/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":"2026-05-25T17:02:42Z","links":{"resolver":"https://pith.science/pith/VOMGLRWXNTHLTXHULXYUAUEEEV","bundle":"https://pith.science/pith/VOMGLRWXNTHLTXHULXYUAUEEEV/bundle.json","state":"https://pith.science/pith/VOMGLRWXNTHLTXHULXYUAUEEEV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VOMGLRWXNTHLTXHULXYUAUEEEV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:VOMGLRWXNTHLTXHULXYUAUEEEV","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":"08ecb6fa6b5be1400e2011d1f13112c06ffe240a0494a095f2029806a6fead9f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-01-25T21:51:28Z","title_canon_sha256":"1608da7a0585d857bceccbe01f5f2cca55affd2163662010e416a404776d5042"},"schema_version":"1.0","source":{"id":"1701.07500","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1701.07500","created_at":"2026-05-18T00:52:03Z"},{"alias_kind":"arxiv_version","alias_value":"1701.07500v1","created_at":"2026-05-18T00:52:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1701.07500","created_at":"2026-05-18T00:52:03Z"},{"alias_kind":"pith_short_12","alias_value":"VOMGLRWXNTHL","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"VOMGLRWXNTHLTXHU","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"VOMGLRWX","created_at":"2026-05-18T12:31:49Z"}],"graph_snapshots":[{"event_id":"sha256:df280592dc264cab1926d666383448c205d393af647c72bb2d7a1a5aa7819d76","target":"graph","created_at":"2026-05-18T00:52:03Z","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":"Power-generating assets (e.g., jet engines, gas turbines) are often instrumented with tens to hundreds of sensors for monitoring physical and performance degradation. Anomaly detection algorithms highlight deviations from predetermined benchmarks with the goal of detecting incipient faults. We are developing an integrated system to address three key challenges within analyzing sensor data from power-generating assets: (1) difficulty in ingesting and analyzing data from large numbers of machines; (2) prevalence of false alarms generated by anomaly detection algorithms resulting in unnecessary d","authors_text":"Chirag Tailor, Duen Horng Chau, Fang Liu, Liexiao Ding, Michael Phillips, Nagi Gebraeel, Paras Jain, Sam Ford","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-01-25T21:51:28Z","title":"Scalable Architecture for Anomaly Detection and Visualization in Power Generating Assets"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1701.07500","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":"sha256:309b5a8eb0a387d7ccb97011348bee8592f4f52516a4fac144f9a0adada98b84","target":"record","created_at":"2026-05-18T00:52:03Z","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":"08ecb6fa6b5be1400e2011d1f13112c06ffe240a0494a095f2029806a6fead9f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-01-25T21:51:28Z","title_canon_sha256":"1608da7a0585d857bceccbe01f5f2cca55affd2163662010e416a404776d5042"},"schema_version":"1.0","source":{"id":"1701.07500","kind":"arxiv","version":1}},"canonical_sha256":"ab9865c6d76cceb9dcf45df14050842547176955c2f430202fe0d74fd9ce006b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ab9865c6d76cceb9dcf45df14050842547176955c2f430202fe0d74fd9ce006b","first_computed_at":"2026-05-18T00:52:03.298758Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:52:03.298758Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HZpvI0M5ic/miucsJU4298CyNKoWHb96srhoCQ6sDuXLw/nLtZINTiSHIJxXNbdGxxClotWsD0JnW9/aIiGDCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:52:03.299383Z","signed_message":"canonical_sha256_bytes"},"source_id":"1701.07500","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:309b5a8eb0a387d7ccb97011348bee8592f4f52516a4fac144f9a0adada98b84","sha256:df280592dc264cab1926d666383448c205d393af647c72bb2d7a1a5aa7819d76"],"state_sha256":"6cdecea6de6455ed579b27a46ef2761be2600f6719e216cded5bcf010351c9ae"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J5aMB+5WSXokgguwKc0aHCuW4rVihGx52XULPIMTV9576LGwiUeR6s8Nj6n8mZMKd01p9AJIqJXlBe3nab0QCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T17:02:42.149963Z","bundle_sha256":"4b3fb73bb51c69d32bfa7b35ff42be39648916b76b887acb30ef3df2bbac2fbc"}}