{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:PBC6EZTNFUAEDNTFNQO225375C","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":"558d4a6cc7662be2b64b4d9f72a173453d421fac3086381c67399399e691b5bc","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2025-06-24T15:10:15Z","title_canon_sha256":"6bcc910e74cd9d365f47b2fb6de25826ba82be0d244c047519bd17139848b7b1"},"schema_version":"1.0","source":{"id":"2506.19698","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.19698","created_at":"2026-07-05T11:26:37Z"},{"alias_kind":"arxiv_version","alias_value":"2506.19698v1","created_at":"2026-07-05T11:26:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.19698","created_at":"2026-07-05T11:26:37Z"},{"alias_kind":"pith_short_12","alias_value":"PBC6EZTNFUAE","created_at":"2026-07-05T11:26:37Z"},{"alias_kind":"pith_short_16","alias_value":"PBC6EZTNFUAEDNTF","created_at":"2026-07-05T11:26:37Z"},{"alias_kind":"pith_short_8","alias_value":"PBC6EZTN","created_at":"2026-07-05T11:26:37Z"}],"graph_snapshots":[{"event_id":"sha256:ddac88ca5fc735fb869a8bd64ebd4621a254b43aaa8d16d24bbb09a6bf7e508a","target":"graph","created_at":"2026-07-05T11:26:37Z","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/2506.19698/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent research increasingly integrates machine learning (ML) into predictive maintenance (PdM) to reduce operational and maintenance costs in data-rich operational settings. However, uncertainty due to model misspecification continues to limit widespread industrial adoption. This paper proposes a PdM framework in which sensor-driven prognostics inform decision-making under economic trade-offs within a finite decision space. We investigate two key questions: (1) Does higher predictive accuracy necessarily lead to better maintenance decisions? (2) If not, how can the impact of prediction errors","authors_text":"Adam Abdin, Yiping Fang, Zhuojun Xie","cross_cats":["math.OC"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2025-06-24T15:10:15Z","title":"Toward Decision-Oriented Prognostics: An Integrated Estimate-Optimize Framework for Predictive Maintenance"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.19698","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":"sha256:3d62c96136635907fd2332ba0ef243f0e4b9d3252a61498accfd7e62007140c4","target":"record","created_at":"2026-07-05T11:26:37Z","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":"558d4a6cc7662be2b64b4d9f72a173453d421fac3086381c67399399e691b5bc","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2025-06-24T15:10:15Z","title_canon_sha256":"6bcc910e74cd9d365f47b2fb6de25826ba82be0d244c047519bd17139848b7b1"},"schema_version":"1.0","source":{"id":"2506.19698","kind":"arxiv","version":1}},"canonical_sha256":"7845e2666d2d0041b6656c1dad777fe8b40320caaa9ee819113c7d061d8acfed","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7845e2666d2d0041b6656c1dad777fe8b40320caaa9ee819113c7d061d8acfed","first_computed_at":"2026-07-05T11:26:37.259484Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:26:37.259484Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vIrllE4yN4e0hKJrSKdUFzvKv1D51MgcMpJd5yguKO4a7x4cPt+h+EJJWYX/3RBRNXhfvjy6pkZbRBANIJseBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:26:37.259976Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.19698","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d62c96136635907fd2332ba0ef243f0e4b9d3252a61498accfd7e62007140c4","sha256:ddac88ca5fc735fb869a8bd64ebd4621a254b43aaa8d16d24bbb09a6bf7e508a"],"state_sha256":"37343e98bf80f4252b4d2d482428bfcfacec94ee3a7580cc03a2015983560e18"}