{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:UC5TKCP7GLE65BV3UFJ5M4NFIH","short_pith_number":"pith:UC5TKCP7","canonical_record":{"source":{"id":"2209.07458","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.acc-ph","submitted_at":"2022-09-15T17:00:33Z","cross_cats_sorted":[],"title_canon_sha256":"b2dfd0b1cc3cbf95ff9ff6f2ddd368ed033b67ede78ef1efa65f6953522b700f","abstract_canon_sha256":"afd7ee1918c42599e2729e1ce205734c57115b0a9dcb422349e4441a4ac4e467"},"schema_version":"1.0"},"canonical_sha256":"a0bb3509ff32c9ee86bba153d671a541dd11bb568e1fb4a465492938dae3e7d7","source":{"kind":"arxiv","id":"2209.07458","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.07458","created_at":"2026-07-05T09:49:57Z"},{"alias_kind":"arxiv_version","alias_value":"2209.07458v3","created_at":"2026-07-05T09:49:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.07458","created_at":"2026-07-05T09:49:57Z"},{"alias_kind":"pith_short_12","alias_value":"UC5TKCP7GLE6","created_at":"2026-07-05T09:49:57Z"},{"alias_kind":"pith_short_16","alias_value":"UC5TKCP7GLE65BV3","created_at":"2026-07-05T09:49:57Z"},{"alias_kind":"pith_short_8","alias_value":"UC5TKCP7","created_at":"2026-07-05T09:49:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:UC5TKCP7GLE65BV3UFJ5M4NFIH","target":"record","payload":{"canonical_record":{"source":{"id":"2209.07458","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.acc-ph","submitted_at":"2022-09-15T17:00:33Z","cross_cats_sorted":[],"title_canon_sha256":"b2dfd0b1cc3cbf95ff9ff6f2ddd368ed033b67ede78ef1efa65f6953522b700f","abstract_canon_sha256":"afd7ee1918c42599e2729e1ce205734c57115b0a9dcb422349e4441a4ac4e467"},"schema_version":"1.0"},"canonical_sha256":"a0bb3509ff32c9ee86bba153d671a541dd11bb568e1fb4a465492938dae3e7d7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:49:57.780554Z","signature_b64":"kB17PxitK5iIK55gWaxd05ETLsiFl3AsUoXGcNByYDt9kCUrhqTm9dJRhluHcrCtS5zFZjqF/KZTQloRY6c0AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a0bb3509ff32c9ee86bba153d671a541dd11bb568e1fb4a465492938dae3e7d7","last_reissued_at":"2026-07-05T09:49:57.780016Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:49:57.780016Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2209.07458","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:49:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ifWMn0Ql3ZbKliFXlfEdSepXOOql3e3EnZ2MeqXproyIpemm5Q6yRB4g7/25cz6GO03w4RsVYe9/239gBVKSAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T06:11:53.635280Z"},"content_sha256":"7fde07667d7097224e5d1149cf1d46a1a5058687d73f2f345377695df417ff53","schema_version":"1.0","event_id":"sha256:7fde07667d7097224e5d1149cf1d46a1a5058687d73f2f345377695df417ff53"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:UC5TKCP7GLE65BV3UFJ5M4NFIH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Uncertainty Aware ML-based surrogate models for particle accelerators: A Study at the Fermilab Booster Accelerator Complex","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.acc-ph","authors_text":"Himanshu Sharma, Jason St. John, Karthik Somayaji Peng Li, Kishansingh Rajput, Malachi Schram","submitted_at":"2022-09-15T17:00:33Z","abstract_excerpt":"Standard deep learning methods, such as Ensemble Models, Bayesian Neural Networks and Quantile Regression Models provide estimates to prediction uncertainties for data-driven deep learning models. However, they can be limited in their applications due to their heavy memory, inference cost, and ability to properly capture out-of-distribution uncertainties. Additionally, some of these models require post-training calibration which limits their ability to be used for continuous learning applications. In this paper, we present a new approach to provide prediction with calibrated uncertainties that"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.07458","kind":"arxiv","version":3},"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/2209.07458/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":"2026-07-05T09:49:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hO7IfBp9LsgQUizhnQ1nyeGz7+l8XLu/Jxnp+Vt/nH1ERYIYHvR55scoT8Xy+2SjcvC2OlnWGEEYzHYouYXrCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T06:11:53.635820Z"},"content_sha256":"e6f6adf14b790c81f3b1e75a061c0cc395be7af7eaea45ae291fcc1f7b18e394","schema_version":"1.0","event_id":"sha256:e6f6adf14b790c81f3b1e75a061c0cc395be7af7eaea45ae291fcc1f7b18e394"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UC5TKCP7GLE65BV3UFJ5M4NFIH/bundle.json","state_url":"https://pith.science/pith/UC5TKCP7GLE65BV3UFJ5M4NFIH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UC5TKCP7GLE65BV3UFJ5M4NFIH/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":"2026-08-19T06:11:53Z","links":{"resolver":"https://pith.science/pith/UC5TKCP7GLE65BV3UFJ5M4NFIH","bundle":"https://pith.science/pith/UC5TKCP7GLE65BV3UFJ5M4NFIH/bundle.json","state":"https://pith.science/pith/UC5TKCP7GLE65BV3UFJ5M4NFIH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UC5TKCP7GLE65BV3UFJ5M4NFIH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:UC5TKCP7GLE65BV3UFJ5M4NFIH","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":"afd7ee1918c42599e2729e1ce205734c57115b0a9dcb422349e4441a4ac4e467","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.acc-ph","submitted_at":"2022-09-15T17:00:33Z","title_canon_sha256":"b2dfd0b1cc3cbf95ff9ff6f2ddd368ed033b67ede78ef1efa65f6953522b700f"},"schema_version":"1.0","source":{"id":"2209.07458","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.07458","created_at":"2026-07-05T09:49:57Z"},{"alias_kind":"arxiv_version","alias_value":"2209.07458v3","created_at":"2026-07-05T09:49:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.07458","created_at":"2026-07-05T09:49:57Z"},{"alias_kind":"pith_short_12","alias_value":"UC5TKCP7GLE6","created_at":"2026-07-05T09:49:57Z"},{"alias_kind":"pith_short_16","alias_value":"UC5TKCP7GLE65BV3","created_at":"2026-07-05T09:49:57Z"},{"alias_kind":"pith_short_8","alias_value":"UC5TKCP7","created_at":"2026-07-05T09:49:57Z"}],"graph_snapshots":[{"event_id":"sha256:e6f6adf14b790c81f3b1e75a061c0cc395be7af7eaea45ae291fcc1f7b18e394","target":"graph","created_at":"2026-07-05T09:49:57Z","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/2209.07458/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Standard deep learning methods, such as Ensemble Models, Bayesian Neural Networks and Quantile Regression Models provide estimates to prediction uncertainties for data-driven deep learning models. However, they can be limited in their applications due to their heavy memory, inference cost, and ability to properly capture out-of-distribution uncertainties. Additionally, some of these models require post-training calibration which limits their ability to be used for continuous learning applications. In this paper, we present a new approach to provide prediction with calibrated uncertainties that","authors_text":"Himanshu Sharma, Jason St. John, Karthik Somayaji Peng Li, Kishansingh Rajput, Malachi Schram","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.acc-ph","submitted_at":"2022-09-15T17:00:33Z","title":"Uncertainty Aware ML-based surrogate models for particle accelerators: A Study at the Fermilab Booster Accelerator Complex"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.07458","kind":"arxiv","version":3},"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":"sha256:7fde07667d7097224e5d1149cf1d46a1a5058687d73f2f345377695df417ff53","target":"record","created_at":"2026-07-05T09:49:57Z","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":"afd7ee1918c42599e2729e1ce205734c57115b0a9dcb422349e4441a4ac4e467","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.acc-ph","submitted_at":"2022-09-15T17:00:33Z","title_canon_sha256":"b2dfd0b1cc3cbf95ff9ff6f2ddd368ed033b67ede78ef1efa65f6953522b700f"},"schema_version":"1.0","source":{"id":"2209.07458","kind":"arxiv","version":3}},"canonical_sha256":"a0bb3509ff32c9ee86bba153d671a541dd11bb568e1fb4a465492938dae3e7d7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a0bb3509ff32c9ee86bba153d671a541dd11bb568e1fb4a465492938dae3e7d7","first_computed_at":"2026-07-05T09:49:57.780016Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:49:57.780016Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kB17PxitK5iIK55gWaxd05ETLsiFl3AsUoXGcNByYDt9kCUrhqTm9dJRhluHcrCtS5zFZjqF/KZTQloRY6c0AA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:49:57.780554Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.07458","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7fde07667d7097224e5d1149cf1d46a1a5058687d73f2f345377695df417ff53","sha256:e6f6adf14b790c81f3b1e75a061c0cc395be7af7eaea45ae291fcc1f7b18e394"],"state_sha256":"edf0a647c6daa897ed8011798283985299278b6fbe2601041c8dfa7f486d83b4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KW/IghJU9BwYd1YvLkXoFihGrXns68+NGOuVGvrQsygKfLREDEOlMytM95EL298VPwnT5qL9BPACeDwaxi+8Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T06:11:53.640534Z","bundle_sha256":"2b9fdade66f3796f802e44c9bdb5e78b850cdfd59bdf3523174568900d4afd6c"}}