{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:DVSO6BGNWAEWWTPA5QX53Z6CBR","short_pith_number":"pith:DVSO6BGN","canonical_record":{"source":{"id":"2605.30593","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-28T21:39:53Z","cross_cats_sorted":["cs.AI","cs.CE"],"title_canon_sha256":"4b8d355d9e14ce6098c5356b55def82745b110c5f1c16556f6094d96023b7c44","abstract_canon_sha256":"30d2769117d2f167ae40d9c3a4846c691e284e421ce992f6557a9b7bbbb40723"},"schema_version":"1.0"},"canonical_sha256":"1d64ef04cdb0096b4de0ec2fdde7c20c7330c49b8c044854dba10b37a35f8bc4","source":{"kind":"arxiv","id":"2605.30593","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30593","created_at":"2026-06-01T01:03:02Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30593v1","created_at":"2026-06-01T01:03:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30593","created_at":"2026-06-01T01:03:02Z"},{"alias_kind":"pith_short_12","alias_value":"DVSO6BGNWAEW","created_at":"2026-06-01T01:03:02Z"},{"alias_kind":"pith_short_16","alias_value":"DVSO6BGNWAEWWTPA","created_at":"2026-06-01T01:03:02Z"},{"alias_kind":"pith_short_8","alias_value":"DVSO6BGN","created_at":"2026-06-01T01:03:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:DVSO6BGNWAEWWTPA5QX53Z6CBR","target":"record","payload":{"canonical_record":{"source":{"id":"2605.30593","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-28T21:39:53Z","cross_cats_sorted":["cs.AI","cs.CE"],"title_canon_sha256":"4b8d355d9e14ce6098c5356b55def82745b110c5f1c16556f6094d96023b7c44","abstract_canon_sha256":"30d2769117d2f167ae40d9c3a4846c691e284e421ce992f6557a9b7bbbb40723"},"schema_version":"1.0"},"canonical_sha256":"1d64ef04cdb0096b4de0ec2fdde7c20c7330c49b8c044854dba10b37a35f8bc4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-01T01:03:02.926088Z","signature_b64":"ZTNuQyiCXfANmc9BLuRJDURbJzocBiCrdm6T+eyqJFxEGGu8n5l9AM7FCH1oF+/NCLCtg+0EB8v0FVopI627Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1d64ef04cdb0096b4de0ec2fdde7c20c7330c49b8c044854dba10b37a35f8bc4","last_reissued_at":"2026-06-01T01:03:02.925137Z","signature_status":"signed_v1","first_computed_at":"2026-06-01T01:03:02.925137Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.30593","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":"2026-06-01T01:03:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c2Bi9AIZJScuPmlrMwwfpcImEhx8FbuZwk+PFRiPgzioAKoaJMjB5I/pqrbEyfcMulh1+F6iP3O4gA3rB4OABA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T22:00:24.105194Z"},"content_sha256":"bb94ad0ae6d13b823ad24fac0c3da36858219c13125dab13bb2fdc94a9c5a933","schema_version":"1.0","event_id":"sha256:bb94ad0ae6d13b823ad24fac0c3da36858219c13125dab13bb2fdc94a9c5a933"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:DVSO6BGNWAEWWTPA5QX53Z6CBR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scientific Machine Learning for Engine Health Management and Remaining Useful Life Prediction","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.CE"],"primary_cat":"cs.LG","authors_text":"Adrian Sandu, Andrew Rimell, Changmin Son, Gavan Burke, James G. Steinrock, Jostein Barry-Straume, Rekha Sundararajan","submitted_at":"2026-05-28T21:39:53Z","abstract_excerpt":"Engine Health Management (EHM) depends on reliable forecasting of Remaining Useful Life (RUL) and on tracking thermal indicators such as turbine gas temperature (TGT). In practice, real-world fleet data are heterogeneous and non-stationary, and point predictions alone are insufficient for risk-aware maintenance decisions. This paper presents a multi-task scientific machine learning framework for turbine prognostics that jointly predicts turbine gas temperature untrimmed (TGTU), Delta Turbine Gas Temperature (DTGT), and RUL, with quantified uncertainty in the form of prediction intervals whose "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30593","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/2605.30593/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-01T01:03:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i3rXTSVQTlc50eouB00hJVo1r6QdpJN0yATQzTR6rz3g8Af2pgHQerwLfH154k+M/rfYkkeAcVKx1FRiZmMtCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T22:00:24.105578Z"},"content_sha256":"0bfc5ed17a9f42f0359eb3cca94648cb647fef23a3736e7fab2ac72dd127819b","schema_version":"1.0","event_id":"sha256:0bfc5ed17a9f42f0359eb3cca94648cb647fef23a3736e7fab2ac72dd127819b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DVSO6BGNWAEWWTPA5QX53Z6CBR/bundle.json","state_url":"https://pith.science/pith/DVSO6BGNWAEWWTPA5QX53Z6CBR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DVSO6BGNWAEWWTPA5QX53Z6CBR/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":"2026-06-26T22:00:24Z","links":{"resolver":"https://pith.science/pith/DVSO6BGNWAEWWTPA5QX53Z6CBR","bundle":"https://pith.science/pith/DVSO6BGNWAEWWTPA5QX53Z6CBR/bundle.json","state":"https://pith.science/pith/DVSO6BGNWAEWWTPA5QX53Z6CBR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DVSO6BGNWAEWWTPA5QX53Z6CBR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DVSO6BGNWAEWWTPA5QX53Z6CBR","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":"30d2769117d2f167ae40d9c3a4846c691e284e421ce992f6557a9b7bbbb40723","cross_cats_sorted":["cs.AI","cs.CE"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-28T21:39:53Z","title_canon_sha256":"4b8d355d9e14ce6098c5356b55def82745b110c5f1c16556f6094d96023b7c44"},"schema_version":"1.0","source":{"id":"2605.30593","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30593","created_at":"2026-06-01T01:03:02Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30593v1","created_at":"2026-06-01T01:03:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30593","created_at":"2026-06-01T01:03:02Z"},{"alias_kind":"pith_short_12","alias_value":"DVSO6BGNWAEW","created_at":"2026-06-01T01:03:02Z"},{"alias_kind":"pith_short_16","alias_value":"DVSO6BGNWAEWWTPA","created_at":"2026-06-01T01:03:02Z"},{"alias_kind":"pith_short_8","alias_value":"DVSO6BGN","created_at":"2026-06-01T01:03:02Z"}],"graph_snapshots":[{"event_id":"sha256:0bfc5ed17a9f42f0359eb3cca94648cb647fef23a3736e7fab2ac72dd127819b","target":"graph","created_at":"2026-06-01T01:03:02Z","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/2605.30593/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Engine Health Management (EHM) depends on reliable forecasting of Remaining Useful Life (RUL) and on tracking thermal indicators such as turbine gas temperature (TGT). In practice, real-world fleet data are heterogeneous and non-stationary, and point predictions alone are insufficient for risk-aware maintenance decisions. This paper presents a multi-task scientific machine learning framework for turbine prognostics that jointly predicts turbine gas temperature untrimmed (TGTU), Delta Turbine Gas Temperature (DTGT), and RUL, with quantified uncertainty in the form of prediction intervals whose ","authors_text":"Adrian Sandu, Andrew Rimell, Changmin Son, Gavan Burke, James G. Steinrock, Jostein Barry-Straume, Rekha Sundararajan","cross_cats":["cs.AI","cs.CE"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-28T21:39:53Z","title":"Scientific Machine Learning for Engine Health Management and Remaining Useful Life Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30593","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:bb94ad0ae6d13b823ad24fac0c3da36858219c13125dab13bb2fdc94a9c5a933","target":"record","created_at":"2026-06-01T01:03:02Z","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":"30d2769117d2f167ae40d9c3a4846c691e284e421ce992f6557a9b7bbbb40723","cross_cats_sorted":["cs.AI","cs.CE"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-28T21:39:53Z","title_canon_sha256":"4b8d355d9e14ce6098c5356b55def82745b110c5f1c16556f6094d96023b7c44"},"schema_version":"1.0","source":{"id":"2605.30593","kind":"arxiv","version":1}},"canonical_sha256":"1d64ef04cdb0096b4de0ec2fdde7c20c7330c49b8c044854dba10b37a35f8bc4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1d64ef04cdb0096b4de0ec2fdde7c20c7330c49b8c044854dba10b37a35f8bc4","first_computed_at":"2026-06-01T01:03:02.925137Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T01:03:02.925137Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZTNuQyiCXfANmc9BLuRJDURbJzocBiCrdm6T+eyqJFxEGGu8n5l9AM7FCH1oF+/NCLCtg+0EB8v0FVopI627Bg==","signature_status":"signed_v1","signed_at":"2026-06-01T01:03:02.926088Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.30593","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb94ad0ae6d13b823ad24fac0c3da36858219c13125dab13bb2fdc94a9c5a933","sha256:0bfc5ed17a9f42f0359eb3cca94648cb647fef23a3736e7fab2ac72dd127819b"],"state_sha256":"7a7ab2fad25bfb2264b2638392326caf382a7f24f2bb026799eb31c7544983ee"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZCsV7hCnw57z7EuXxkF+bhW5Nv2W09ShwNuIxNQN6t2SRNmOCRsPfCSweay1eu5FXRPNJWDcdIZ8NayOsUZKBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T22:00:24.107531Z","bundle_sha256":"4fd98e82a2bae2cccf006ea947cfa7873e4322c28b271b6e3d7503b22faaf18d"}}