{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:5YAYLOATBHJVMAVZD53JLZBI24","short_pith_number":"pith:5YAYLOAT","canonical_record":{"source":{"id":"2605.12768","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2026-05-12T21:31:32Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5d4065676ca092e10c1ecf3c9e7637affe29efaa6c8f0776bb888613ce2e1be4","abstract_canon_sha256":"d21a8dc6abaa56471212dc8bdb6106d5d337ae3eddad736e37d8c62874459d33"},"schema_version":"1.0"},"canonical_sha256":"ee0185b81309d35602b91f7695e428d734820623abbfe69c91d8b0bbd09f5ebf","source":{"kind":"arxiv","id":"2605.12768","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.12768","created_at":"2026-05-18T03:09:48Z"},{"alias_kind":"arxiv_version","alias_value":"2605.12768v1","created_at":"2026-05-18T03:09:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.12768","created_at":"2026-05-18T03:09:48Z"},{"alias_kind":"pith_short_12","alias_value":"5YAYLOATBHJV","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"5YAYLOATBHJVMAVZ","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"5YAYLOAT","created_at":"2026-05-18T12:33:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:5YAYLOATBHJVMAVZD53JLZBI24","target":"record","payload":{"canonical_record":{"source":{"id":"2605.12768","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2026-05-12T21:31:32Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5d4065676ca092e10c1ecf3c9e7637affe29efaa6c8f0776bb888613ce2e1be4","abstract_canon_sha256":"d21a8dc6abaa56471212dc8bdb6106d5d337ae3eddad736e37d8c62874459d33"},"schema_version":"1.0"},"canonical_sha256":"ee0185b81309d35602b91f7695e428d734820623abbfe69c91d8b0bbd09f5ebf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:09:48.175764Z","signature_b64":"dci2v/TAiE+LMdQxH2EAXSjVSJ0K4OzAGbk+mmkr7iQjXPGYzqqAzZ6O3Nw9mVvZFR+l1qsM5KaO0lxvES8IAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ee0185b81309d35602b91f7695e428d734820623abbfe69c91d8b0bbd09f5ebf","last_reissued_at":"2026-05-18T03:09:48.174830Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:09:48.174830Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.12768","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":"2026-05-18T03:09:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2PLrrvrvnynrmAkQh57qfXe52XlJ2rPBQU6om0lS2Gwu8RWZhS35ytcSYbnC7V08avE4J1UR1c/O+Ek9A/3mDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T23:46:24.900595Z"},"content_sha256":"919f38f20e38590cf6e8d1fe6049f9579e2d556150754bd9e738c475bff5f9a3","schema_version":"1.0","event_id":"sha256:919f38f20e38590cf6e8d1fe6049f9579e2d556150754bd9e738c475bff5f9a3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:5YAYLOATBHJVMAVZD53JLZBI24","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ISOMORPH: A Supply Chain Digital Twin for Simulation, Dataset Generation, and Forecasting Benchmarks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"ISOMORPH creates the first public digital twin of a multi-echelon supply chain to generate forecasting benchmarks and test foundation models.","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Benjamin J. Zhang, Daniel Elenius, Houman Owhadi, Hyemin Gu, Markos A. Katsoulakis, Michael Tyrrell, Theo J. Bourdais, Tuhin Sahai, Zhizhen Zhang","submitted_at":"2026-05-12T21:31:32Z","abstract_excerpt":"Open time-series forecasting (TSF) benchmarks cover retail, energy, weather, and traffic, but supply-chain logistics remains underserved. We introduce ISOMORPH, the first public digital twin of a multi-echelon logistics network with fully interpretable, user-configurable parameters and modular topology, demand process, and control rules. The simulator advances a directed routing graph in discrete time: demand arrives at the destination, is served from stock or recorded as backlog, and triggers replenishment through the network. The state vector tracks per-node on-hand inventory with outstandin"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Zero-shot evaluation of four foundation models (Chronos, Moirai, TimesFM, Lag-Llama) shows MASE values exceeding public GIFT-Eval references at low-to-moderate horizons, supporting incorporation into existing benchmarks. The same pairing produces forecast confidence bands via Latin-hypercube perturbation of demand-side knobs, demonstrating that foundation models can serve as fast surrogates for the digital twin's forward UQ.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The simulator's discrete-time rules and state vector produce dynamics that accurately reproduce real supply-chain phenomena such as the bullwhip effect at empirically consistent magnitudes, without direct calibration or validation against proprietary operational data.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"ISOMORPH is a modular digital twin simulator for supply chain networks that releases datasets exhibiting variance amplification and regime shifts for benchmarking forecasting models and performing forward uncertainty quantification.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"ISOMORPH creates the first public digital twin of a multi-echelon supply chain to generate forecasting benchmarks and test foundation models.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"781274ed611982d4dda410bb9dd0c119848e43caccd17e95b013fdeb56a5b932"},"source":{"id":"2605.12768","kind":"arxiv","version":1},"verdict":{"id":"5e56188f-6e81-4e97-9c4c-4dd54b33a4a1","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-14T19:27:59.066766Z","strongest_claim":"Zero-shot evaluation of four foundation models (Chronos, Moirai, TimesFM, Lag-Llama) shows MASE values exceeding public GIFT-Eval references at low-to-moderate horizons, supporting incorporation into existing benchmarks. The same pairing produces forecast confidence bands via Latin-hypercube perturbation of demand-side knobs, demonstrating that foundation models can serve as fast surrogates for the digital twin's forward UQ.","one_line_summary":"ISOMORPH is a modular digital twin simulator for supply chain networks that releases datasets exhibiting variance amplification and regime shifts for benchmarking forecasting models and performing forward uncertainty quantification.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The simulator's discrete-time rules and state vector produce dynamics that accurately reproduce real supply-chain phenomena such as the bullwhip effect at empirically consistent magnitudes, without direct calibration or validation against proprietary operational data.","pith_extraction_headline":"ISOMORPH creates the first public digital twin of a multi-echelon supply chain to generate forecasting benchmarks and test foundation models."},"references":{"count":12,"sample":[{"doi":"10.48550/arxiv.2604.13478","year":null,"title":"Deepbullwhip: An Open-Source Simulation and Benchmarking for Multi-Echelon Bullwhip Analyses","work_id":"bcb8b036-6373-448a-a602-758ac436033a","ref_index":1,"cited_arxiv_id":"2604.13478","is_internal_anchor":true},{"doi":"10.1103/physrevlett.126.098302","year":null,"title":"Enforcing analytic constraints in neural networks emulating physical systems.Physical Review Letters, 126(9), March 2021","work_id":"6af60857-bcab-43bf-97de-9b4c22d8a596","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1287/msom.1060.0149","year":null,"title":"Hong Chen and David D","work_id":"bdcb174c-cd8f-473e-9487-c49e20ee8b42","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2008,"title":"24 Christian D","work_id":"a4a8574a-310c-42f7-a350-eba4fed8b087","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1016/j.ijforecast.2019.04.014","year":2019,"title":"URL https://www.sciencedirect.com/science/article/ pii/S0169207019301128","work_id":"91591d05-2e2a-4c6f-b3f7-f2dc09a99e3e","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":12,"snapshot_sha256":"64c7e88b980eac78f4ab9d6d9a05835264a77df62a99810f3c7c3debf314c2fb","internal_anchors":1},"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":"5e56188f-6e81-4e97-9c4c-4dd54b33a4a1"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:09:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s90sQFzdbI8qp4a134KT3KeJPrSQIKGKxGstbUnZKoUXV+ZlFMkDYFFZeHbNQLa4tuphWsB/lthiuH7sJ7mvBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T23:46:24.901532Z"},"content_sha256":"dedd844dc0b8bfcb318423286f0028b466a663e879f997ab2f3672aff61fd592","schema_version":"1.0","event_id":"sha256:dedd844dc0b8bfcb318423286f0028b466a663e879f997ab2f3672aff61fd592"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5YAYLOATBHJVMAVZD53JLZBI24/bundle.json","state_url":"https://pith.science/pith/5YAYLOATBHJVMAVZD53JLZBI24/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5YAYLOATBHJVMAVZD53JLZBI24/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":"2026-05-26T23:46:24Z","links":{"resolver":"https://pith.science/pith/5YAYLOATBHJVMAVZD53JLZBI24","bundle":"https://pith.science/pith/5YAYLOATBHJVMAVZD53JLZBI24/bundle.json","state":"https://pith.science/pith/5YAYLOATBHJVMAVZD53JLZBI24/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5YAYLOATBHJVMAVZD53JLZBI24/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:5YAYLOATBHJVMAVZD53JLZBI24","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":"d21a8dc6abaa56471212dc8bdb6106d5d337ae3eddad736e37d8c62874459d33","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2026-05-12T21:31:32Z","title_canon_sha256":"5d4065676ca092e10c1ecf3c9e7637affe29efaa6c8f0776bb888613ce2e1be4"},"schema_version":"1.0","source":{"id":"2605.12768","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.12768","created_at":"2026-05-18T03:09:48Z"},{"alias_kind":"arxiv_version","alias_value":"2605.12768v1","created_at":"2026-05-18T03:09:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.12768","created_at":"2026-05-18T03:09:48Z"},{"alias_kind":"pith_short_12","alias_value":"5YAYLOATBHJV","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"5YAYLOATBHJVMAVZ","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"5YAYLOAT","created_at":"2026-05-18T12:33:37Z"}],"graph_snapshots":[{"event_id":"sha256:dedd844dc0b8bfcb318423286f0028b466a663e879f997ab2f3672aff61fd592","target":"graph","created_at":"2026-05-18T03:09:48Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"Zero-shot evaluation of four foundation models (Chronos, Moirai, TimesFM, Lag-Llama) shows MASE values exceeding public GIFT-Eval references at low-to-moderate horizons, supporting incorporation into existing benchmarks. The same pairing produces forecast confidence bands via Latin-hypercube perturbation of demand-side knobs, demonstrating that foundation models can serve as fast surrogates for the digital twin's forward UQ."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"The simulator's discrete-time rules and state vector produce dynamics that accurately reproduce real supply-chain phenomena such as the bullwhip effect at empirically consistent magnitudes, without direct calibration or validation against proprietary operational data."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"ISOMORPH is a modular digital twin simulator for supply chain networks that releases datasets exhibiting variance amplification and regime shifts for benchmarking forecasting models and performing forward uncertainty quantification."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"ISOMORPH creates the first public digital twin of a multi-echelon supply chain to generate forecasting benchmarks and test foundation models."}],"snapshot_sha256":"781274ed611982d4dda410bb9dd0c119848e43caccd17e95b013fdeb56a5b932"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Open time-series forecasting (TSF) benchmarks cover retail, energy, weather, and traffic, but supply-chain logistics remains underserved. We introduce ISOMORPH, the first public digital twin of a multi-echelon logistics network with fully interpretable, user-configurable parameters and modular topology, demand process, and control rules. The simulator advances a directed routing graph in discrete time: demand arrives at the destination, is served from stock or recorded as backlog, and triggers replenishment through the network. The state vector tracks per-node on-hand inventory with outstandin","authors_text":"Benjamin J. Zhang, Daniel Elenius, Houman Owhadi, Hyemin Gu, Markos A. Katsoulakis, Michael Tyrrell, Theo J. Bourdais, Tuhin Sahai, Zhizhen Zhang","cross_cats":["cs.LG"],"headline":"ISOMORPH creates the first public digital twin of a multi-echelon supply chain to generate forecasting benchmarks and test foundation models.","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2026-05-12T21:31:32Z","title":"ISOMORPH: A Supply Chain Digital Twin for Simulation, Dataset Generation, and Forecasting Benchmarks"},"references":{"count":12,"internal_anchors":1,"resolved_work":12,"sample":[{"cited_arxiv_id":"2604.13478","doi":"10.48550/arxiv.2604.13478","is_internal_anchor":true,"ref_index":1,"title":"Deepbullwhip: An Open-Source Simulation and Benchmarking for Multi-Echelon Bullwhip Analyses","work_id":"bcb8b036-6373-448a-a602-758ac436033a","year":null},{"cited_arxiv_id":"","doi":"10.1103/physrevlett.126.098302","is_internal_anchor":false,"ref_index":2,"title":"Enforcing analytic constraints in neural networks emulating physical systems.Physical Review Letters, 126(9), March 2021","work_id":"6af60857-bcab-43bf-97de-9b4c22d8a596","year":null},{"cited_arxiv_id":"","doi":"10.1287/msom.1060.0149","is_internal_anchor":false,"ref_index":3,"title":"Hong Chen and David D","work_id":"bdcb174c-cd8f-473e-9487-c49e20ee8b42","year":null},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"24 Christian D","work_id":"a4a8574a-310c-42f7-a350-eba4fed8b087","year":2008},{"cited_arxiv_id":"","doi":"10.1016/j.ijforecast.2019.04.014","is_internal_anchor":false,"ref_index":5,"title":"URL https://www.sciencedirect.com/science/article/ pii/S0169207019301128","work_id":"91591d05-2e2a-4c6f-b3f7-f2dc09a99e3e","year":2019}],"snapshot_sha256":"64c7e88b980eac78f4ab9d6d9a05835264a77df62a99810f3c7c3debf314c2fb"},"source":{"id":"2605.12768","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-14T19:27:59.066766Z","id":"5e56188f-6e81-4e97-9c4c-4dd54b33a4a1","model_set":{"reader":"grok-4.3"},"one_line_summary":"ISOMORPH is a modular digital twin simulator for supply chain networks that releases datasets exhibiting variance amplification and regime shifts for benchmarking forecasting models and performing forward uncertainty quantification.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"ISOMORPH creates the first public digital twin of a multi-echelon supply chain to generate forecasting benchmarks and test foundation models.","strongest_claim":"Zero-shot evaluation of four foundation models (Chronos, Moirai, TimesFM, Lag-Llama) shows MASE values exceeding public GIFT-Eval references at low-to-moderate horizons, supporting incorporation into existing benchmarks. The same pairing produces forecast confidence bands via Latin-hypercube perturbation of demand-side knobs, demonstrating that foundation models can serve as fast surrogates for the digital twin's forward UQ.","weakest_assumption":"The simulator's discrete-time rules and state vector produce dynamics that accurately reproduce real supply-chain phenomena such as the bullwhip effect at empirically consistent magnitudes, without direct calibration or validation against proprietary operational data."}},"verdict_id":"5e56188f-6e81-4e97-9c4c-4dd54b33a4a1"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:919f38f20e38590cf6e8d1fe6049f9579e2d556150754bd9e738c475bff5f9a3","target":"record","created_at":"2026-05-18T03:09:48Z","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":"d21a8dc6abaa56471212dc8bdb6106d5d337ae3eddad736e37d8c62874459d33","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2026-05-12T21:31:32Z","title_canon_sha256":"5d4065676ca092e10c1ecf3c9e7637affe29efaa6c8f0776bb888613ce2e1be4"},"schema_version":"1.0","source":{"id":"2605.12768","kind":"arxiv","version":1}},"canonical_sha256":"ee0185b81309d35602b91f7695e428d734820623abbfe69c91d8b0bbd09f5ebf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ee0185b81309d35602b91f7695e428d734820623abbfe69c91d8b0bbd09f5ebf","first_computed_at":"2026-05-18T03:09:48.174830Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:09:48.174830Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dci2v/TAiE+LMdQxH2EAXSjVSJ0K4OzAGbk+mmkr7iQjXPGYzqqAzZ6O3Nw9mVvZFR+l1qsM5KaO0lxvES8IAg==","signature_status":"signed_v1","signed_at":"2026-05-18T03:09:48.175764Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.12768","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:919f38f20e38590cf6e8d1fe6049f9579e2d556150754bd9e738c475bff5f9a3","sha256:dedd844dc0b8bfcb318423286f0028b466a663e879f997ab2f3672aff61fd592"],"state_sha256":"27775d796260335955df8a96063befc15922b0ac67997348ba93122e8dffc282"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rc86TiAePij2wA8sE7YFOf535yWKDESAq13xn6vOanKIKtDV+82FeF5Bx85/RBfto9gLxR354Pa7hyqq5jZADw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T23:46:24.905391Z","bundle_sha256":"6f793a7bfc9d1abb1f4e57d2eb9a6f6c2dcd8974372fc84f4381438040259523"}}