{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:6G7HNJSFX3LJG3UQPS47BEM22S","short_pith_number":"pith:6G7HNJSF","canonical_record":{"source":{"id":"2605.15719","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.ET","submitted_at":"2026-05-15T08:15:15Z","cross_cats_sorted":[],"title_canon_sha256":"ec7ce4942fa6c9bf2cc38f168794dff008395c90606e9097c6a1427393c1b634","abstract_canon_sha256":"0734f4f7ad89f241d5aaf5d2ad021074db33adac0ac70d1ab3ee8f6f4d8cfa89"},"schema_version":"1.0"},"canonical_sha256":"f1be76a645bed6936e907cb9f0919ad493b2f5d7aba69d3d8c9fa45cfd92d118","source":{"kind":"arxiv","id":"2605.15719","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.15719","created_at":"2026-05-20T00:01:14Z"},{"alias_kind":"arxiv_version","alias_value":"2605.15719v1","created_at":"2026-05-20T00:01:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.15719","created_at":"2026-05-20T00:01:14Z"},{"alias_kind":"pith_short_12","alias_value":"6G7HNJSFX3LJ","created_at":"2026-05-20T00:01:14Z"},{"alias_kind":"pith_short_16","alias_value":"6G7HNJSFX3LJG3UQ","created_at":"2026-05-20T00:01:14Z"},{"alias_kind":"pith_short_8","alias_value":"6G7HNJSF","created_at":"2026-05-20T00:01:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:6G7HNJSFX3LJG3UQPS47BEM22S","target":"record","payload":{"canonical_record":{"source":{"id":"2605.15719","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.ET","submitted_at":"2026-05-15T08:15:15Z","cross_cats_sorted":[],"title_canon_sha256":"ec7ce4942fa6c9bf2cc38f168794dff008395c90606e9097c6a1427393c1b634","abstract_canon_sha256":"0734f4f7ad89f241d5aaf5d2ad021074db33adac0ac70d1ab3ee8f6f4d8cfa89"},"schema_version":"1.0"},"canonical_sha256":"f1be76a645bed6936e907cb9f0919ad493b2f5d7aba69d3d8c9fa45cfd92d118","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:01:14.528715Z","signature_b64":"w2ixiq5C2KLTGTMIhgFAh/Rz8xe7KalUnio6hRKiQ4IET49NXZ2KPhp702YMRKVztRQg66LmXz8a7CbF4FhsBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f1be76a645bed6936e907cb9f0919ad493b2f5d7aba69d3d8c9fa45cfd92d118","last_reissued_at":"2026-05-20T00:01:14.527697Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:01:14.527697Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.15719","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":"2026-05-20T00:01:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M+RNC20KjeJBCPeoMEqLrczR9r3z/xP3+fh5H6RipvFh3HMLKwYjqDONXtROQcniQXznmsRvbvxiJWTjdi5vCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T11:01:03.605380Z"},"content_sha256":"501be26e5018d4aa8a0d216df5a1b3ed5dd1cecb1573fcf322d0ad7fee944cf8","schema_version":"1.0","event_id":"sha256:501be26e5018d4aa8a0d216df5a1b3ed5dd1cecb1573fcf322d0ad7fee944cf8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:6G7HNJSFX3LJG3UQPS47BEM22S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Lightweight Cross-Device Sleep Tracking on the WeBe Wearable Platform","license":"http://creativecommons.org/licenses/by/4.0/","headline":"A simple pipeline on raw accelerometer signals tracks sleep across wearables with 27 to 42 minute error","cross_cats":[],"primary_cat":"cs.ET","authors_text":"Ehsan Kourkchi, Houman Homayoun, Krishi Prashant Shah, Setareh Rafatirad, Wei Shao, Zequan Liang","submitted_at":"2026-05-15T08:15:15Z","abstract_excerpt":"Wearable devices are widely used for continuous health monitoring, yet reliable sleep tracking on emerging platforms remains underexplored due to reliance on proprietary algorithms and device-specific activity representations. We present a lightweight and reproducible sleep tracking pipeline that operates directly on raw accelerometer signals. The method converts data into epoch-level activity features, applies temporal smoothing and normalized scoring, and performs sleep/wake classification using a globally calibrated threshold. We calibrate the model on the Multilevel Monitoring of Activity "},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"The lightweight pipeline achieves a mean absolute error of 41.6 minutes in Total Sleep Time on MMASH and 27.4 minutes on real-world WeBe data from three participants, demonstrating accurate and generalizable sleep tracking using a simple and reproducible pipeline.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That a single globally calibrated threshold applied after normalized scoring on epoch-level activity features will generalize across different wearable hardware, participant populations, and real-world conditions without device-specific retraining or post-hoc adjustments.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Lightweight pipeline converts raw accelerometer data to epoch features, applies smoothing and normalized scoring, then uses a globally calibrated threshold for sleep/wake classification, reporting TST errors of 27-42 minutes on MMASH and WeBe data.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"A simple pipeline on raw accelerometer signals tracks sleep across wearables with 27 to 42 minute error","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"0ba7e9efe91857bbc0d9804207df1dbd11df9e63c03b417c0fe991f34b9f4e17"},"source":{"id":"2605.15719","kind":"arxiv","version":1},"verdict":{"id":"2ef3501f-46bc-4b6a-825e-7720ce5c2e06","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T18:15:08.890349Z","strongest_claim":"The lightweight pipeline achieves a mean absolute error of 41.6 minutes in Total Sleep Time on MMASH and 27.4 minutes on real-world WeBe data from three participants, demonstrating accurate and generalizable sleep tracking using a simple and reproducible pipeline.","one_line_summary":"Lightweight pipeline converts raw accelerometer data to epoch features, applies smoothing and normalized scoring, then uses a globally calibrated threshold for sleep/wake classification, reporting TST errors of 27-42 minutes on MMASH and WeBe data.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That a single globally calibrated threshold applied after normalized scoring on epoch-level activity features will generalize across different wearable hardware, participant populations, and real-world conditions without device-specific retraining or post-hoc adjustments.","pith_extraction_headline":"A simple pipeline on raw accelerometer signals tracks sleep across wearables with 27 to 42 minute error"},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.15719/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T19:33:25.322034Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_title_agreement","ran_at":"2026-05-19T18:31:18.796811Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T18:21:42.517339Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T17:21:56.009510Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"aafab9c14a306a32398557b65aaba9b58282c5dfa089ac9fec3282ee4b69fe9a"},"references":{"count":19,"sample":[{"doi":"","year":2006,"title":"Christine Acebo and Monique K LeBourgeois. 2006. Actigraphy.Respiratory care clinics of North America12, 1 (2006), 23–30","work_id":"6ca1677a-4896-4aaf-a2a6-ad74b25b9431","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2026,"title":"Ametris. 2026. ActiGraph LEAP | Ametris Wearable Devices. https://ametris. com/actigraph-leap. [Online; accessed May 2026]","work_id":"f52220e7-a36d-427b-a1a7-a5e9e93604d8","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2007,"title":"Greg Atkinson and Damien Davenne. 2007. Relationships between sleep, physical activity and human health.Physiology & behavior90, 2-3 (2007), 229–235","work_id":"6f6cd747-dcb6-4726-8652-9c9736c62d4f","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":1992,"title":"Roger J Cole, Daniel F Kripke, William Gruen, Daniel J Mullaney, and J Christian Gillin. 1992. Automatic sleep/wake identification from wrist activity.Sleep15, 5 (1992), 461–469","work_id":"d825c558-5520-493e-80b3-9a66aa4795e7","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2019,"title":"Massimiliano De Zambotti, Nicola Cellini, Aimee Goldstone, Ian M Colrain, and Fiona C Baker. 2019. Wearable sleep technology in clinical and research settings. Medicine and science in sports and exerc","work_id":"1262a398-79fd-4b57-92d0-027a06286572","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":19,"snapshot_sha256":"03812347420215e1033f099eb7ebca947c6f40381a8b5930da99c9966777af7a","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":"2ef3501f-46bc-4b6a-825e-7720ce5c2e06"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T00:01:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XRMzMGi7MSzO8T7jCV6+Bo6mf/l2nOc1VpUTAyLpHM6U2vYYOLXS0ElZM3bETulV6XDhX/3FnkK9xjxAxQA4Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T11:01:03.606853Z"},"content_sha256":"c61683a4eaf6f4c7f7acb7915fbf6655da07f911377bc7ed089dd8c1edd59106","schema_version":"1.0","event_id":"sha256:c61683a4eaf6f4c7f7acb7915fbf6655da07f911377bc7ed089dd8c1edd59106"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6G7HNJSFX3LJG3UQPS47BEM22S/bundle.json","state_url":"https://pith.science/pith/6G7HNJSFX3LJG3UQPS47BEM22S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6G7HNJSFX3LJG3UQPS47BEM22S/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":"2026-05-25T11:01:03Z","links":{"resolver":"https://pith.science/pith/6G7HNJSFX3LJG3UQPS47BEM22S","bundle":"https://pith.science/pith/6G7HNJSFX3LJG3UQPS47BEM22S/bundle.json","state":"https://pith.science/pith/6G7HNJSFX3LJG3UQPS47BEM22S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6G7HNJSFX3LJG3UQPS47BEM22S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:6G7HNJSFX3LJG3UQPS47BEM22S","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":"0734f4f7ad89f241d5aaf5d2ad021074db33adac0ac70d1ab3ee8f6f4d8cfa89","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.ET","submitted_at":"2026-05-15T08:15:15Z","title_canon_sha256":"ec7ce4942fa6c9bf2cc38f168794dff008395c90606e9097c6a1427393c1b634"},"schema_version":"1.0","source":{"id":"2605.15719","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.15719","created_at":"2026-05-20T00:01:14Z"},{"alias_kind":"arxiv_version","alias_value":"2605.15719v1","created_at":"2026-05-20T00:01:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.15719","created_at":"2026-05-20T00:01:14Z"},{"alias_kind":"pith_short_12","alias_value":"6G7HNJSFX3LJ","created_at":"2026-05-20T00:01:14Z"},{"alias_kind":"pith_short_16","alias_value":"6G7HNJSFX3LJG3UQ","created_at":"2026-05-20T00:01:14Z"},{"alias_kind":"pith_short_8","alias_value":"6G7HNJSF","created_at":"2026-05-20T00:01:14Z"}],"graph_snapshots":[{"event_id":"sha256:c61683a4eaf6f4c7f7acb7915fbf6655da07f911377bc7ed089dd8c1edd59106","target":"graph","created_at":"2026-05-20T00:01:14Z","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":"The lightweight pipeline achieves a mean absolute error of 41.6 minutes in Total Sleep Time on MMASH and 27.4 minutes on real-world WeBe data from three participants, demonstrating accurate and generalizable sleep tracking using a simple and reproducible pipeline."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That a single globally calibrated threshold applied after normalized scoring on epoch-level activity features will generalize across different wearable hardware, participant populations, and real-world conditions without device-specific retraining or post-hoc adjustments."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"Lightweight pipeline converts raw accelerometer data to epoch features, applies smoothing and normalized scoring, then uses a globally calibrated threshold for sleep/wake classification, reporting TST errors of 27-42 minutes on MMASH and WeBe data."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"A simple pipeline on raw accelerometer signals tracks sleep across wearables with 27 to 42 minute error"}],"snapshot_sha256":"0ba7e9efe91857bbc0d9804207df1dbd11df9e63c03b417c0fe991f34b9f4e17"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T19:33:25.322034Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"doi_title_agreement","ran_at":"2026-05-19T18:31:18.796811Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"doi_compliance","ran_at":"2026-05-19T18:21:42.517339Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T17:21:56.009510Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2605.15719/integrity.json","findings":[],"snapshot_sha256":"aafab9c14a306a32398557b65aaba9b58282c5dfa089ac9fec3282ee4b69fe9a","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Wearable devices are widely used for continuous health monitoring, yet reliable sleep tracking on emerging platforms remains underexplored due to reliance on proprietary algorithms and device-specific activity representations. We present a lightweight and reproducible sleep tracking pipeline that operates directly on raw accelerometer signals. The method converts data into epoch-level activity features, applies temporal smoothing and normalized scoring, and performs sleep/wake classification using a globally calibrated threshold. We calibrate the model on the Multilevel Monitoring of Activity ","authors_text":"Ehsan Kourkchi, Houman Homayoun, Krishi Prashant Shah, Setareh Rafatirad, Wei Shao, Zequan Liang","cross_cats":[],"headline":"A simple pipeline on raw accelerometer signals tracks sleep across wearables with 27 to 42 minute error","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.ET","submitted_at":"2026-05-15T08:15:15Z","title":"Lightweight Cross-Device Sleep Tracking on the WeBe Wearable Platform"},"references":{"count":19,"internal_anchors":0,"resolved_work":19,"sample":[{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":1,"title":"Christine Acebo and Monique K LeBourgeois. 2006. Actigraphy.Respiratory care clinics of North America12, 1 (2006), 23–30","work_id":"6ca1677a-4896-4aaf-a2a6-ad74b25b9431","year":2006},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":2,"title":"Ametris. 2026. ActiGraph LEAP | Ametris Wearable Devices. https://ametris. com/actigraph-leap. [Online; accessed May 2026]","work_id":"f52220e7-a36d-427b-a1a7-a5e9e93604d8","year":2026},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":3,"title":"Greg Atkinson and Damien Davenne. 2007. Relationships between sleep, physical activity and human health.Physiology & behavior90, 2-3 (2007), 229–235","work_id":"6f6cd747-dcb6-4726-8652-9c9736c62d4f","year":2007},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"Roger J Cole, Daniel F Kripke, William Gruen, Daniel J Mullaney, and J Christian Gillin. 1992. Automatic sleep/wake identification from wrist activity.Sleep15, 5 (1992), 461–469","work_id":"d825c558-5520-493e-80b3-9a66aa4795e7","year":1992},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"title":"Massimiliano De Zambotti, Nicola Cellini, Aimee Goldstone, Ian M Colrain, and Fiona C Baker. 2019. Wearable sleep technology in clinical and research settings. Medicine and science in sports and exerc","work_id":"1262a398-79fd-4b57-92d0-027a06286572","year":2019}],"snapshot_sha256":"03812347420215e1033f099eb7ebca947c6f40381a8b5930da99c9966777af7a"},"source":{"id":"2605.15719","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-19T18:15:08.890349Z","id":"2ef3501f-46bc-4b6a-825e-7720ce5c2e06","model_set":{"reader":"grok-4.3"},"one_line_summary":"Lightweight pipeline converts raw accelerometer data to epoch features, applies smoothing and normalized scoring, then uses a globally calibrated threshold for sleep/wake classification, reporting TST errors of 27-42 minutes on MMASH and WeBe data.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"A simple pipeline on raw accelerometer signals tracks sleep across wearables with 27 to 42 minute error","strongest_claim":"The lightweight pipeline achieves a mean absolute error of 41.6 minutes in Total Sleep Time on MMASH and 27.4 minutes on real-world WeBe data from three participants, demonstrating accurate and generalizable sleep tracking using a simple and reproducible pipeline.","weakest_assumption":"That a single globally calibrated threshold applied after normalized scoring on epoch-level activity features will generalize across different wearable hardware, participant populations, and real-world conditions without device-specific retraining or post-hoc adjustments."}},"verdict_id":"2ef3501f-46bc-4b6a-825e-7720ce5c2e06"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:501be26e5018d4aa8a0d216df5a1b3ed5dd1cecb1573fcf322d0ad7fee944cf8","target":"record","created_at":"2026-05-20T00:01:14Z","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":"0734f4f7ad89f241d5aaf5d2ad021074db33adac0ac70d1ab3ee8f6f4d8cfa89","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.ET","submitted_at":"2026-05-15T08:15:15Z","title_canon_sha256":"ec7ce4942fa6c9bf2cc38f168794dff008395c90606e9097c6a1427393c1b634"},"schema_version":"1.0","source":{"id":"2605.15719","kind":"arxiv","version":1}},"canonical_sha256":"f1be76a645bed6936e907cb9f0919ad493b2f5d7aba69d3d8c9fa45cfd92d118","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f1be76a645bed6936e907cb9f0919ad493b2f5d7aba69d3d8c9fa45cfd92d118","first_computed_at":"2026-05-20T00:01:14.527697Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:01:14.527697Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"w2ixiq5C2KLTGTMIhgFAh/Rz8xe7KalUnio6hRKiQ4IET49NXZ2KPhp702YMRKVztRQg66LmXz8a7CbF4FhsBQ==","signature_status":"signed_v1","signed_at":"2026-05-20T00:01:14.528715Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.15719","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:501be26e5018d4aa8a0d216df5a1b3ed5dd1cecb1573fcf322d0ad7fee944cf8","sha256:c61683a4eaf6f4c7f7acb7915fbf6655da07f911377bc7ed089dd8c1edd59106"],"state_sha256":"3803f6074c4743d0e454b9e31dc75fb883694c249313b8fcfed8164eec473d27"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VghOPCvUAi1xm657rrj6R7C+5+rZTt0JILY/uwKq5tq4KVgXZKZpfLoI8HWFvQ7ASkrdBXYAIKh6caQOA+fmCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T11:01:03.612392Z","bundle_sha256":"6aaf444e26af232636eb071a196291bd03db88dcb9f6d6653ea4473206965063"}}