{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:OOLLWAIXFIMRGKAFNT43MKVVDK","short_pith_number":"pith:OOLLWAIX","canonical_record":{"source":{"id":"2605.17263","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2026-05-17T05:11:31Z","cross_cats_sorted":[],"title_canon_sha256":"a43e1389c7ee6d25af2cef4ab7e69080a80ddfbcdd378a64118dd33f7b8e24fe","abstract_canon_sha256":"15a9b040b6e1bfce0aea173097923b88b5cec4767ae26d05cc4365bd93e956f1"},"schema_version":"1.0"},"canonical_sha256":"7396bb01172a191328056cf9b62ab51a804654ff5f32bcbc634300b8ee682831","source":{"kind":"arxiv","id":"2605.17263","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.17263","created_at":"2026-05-20T00:03:48Z"},{"alias_kind":"arxiv_version","alias_value":"2605.17263v1","created_at":"2026-05-20T00:03:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17263","created_at":"2026-05-20T00:03:48Z"},{"alias_kind":"pith_short_12","alias_value":"OOLLWAIXFIMR","created_at":"2026-05-20T00:03:48Z"},{"alias_kind":"pith_short_16","alias_value":"OOLLWAIXFIMRGKAF","created_at":"2026-05-20T00:03:48Z"},{"alias_kind":"pith_short_8","alias_value":"OOLLWAIX","created_at":"2026-05-20T00:03:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:OOLLWAIXFIMRGKAFNT43MKVVDK","target":"record","payload":{"canonical_record":{"source":{"id":"2605.17263","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2026-05-17T05:11:31Z","cross_cats_sorted":[],"title_canon_sha256":"a43e1389c7ee6d25af2cef4ab7e69080a80ddfbcdd378a64118dd33f7b8e24fe","abstract_canon_sha256":"15a9b040b6e1bfce0aea173097923b88b5cec4767ae26d05cc4365bd93e956f1"},"schema_version":"1.0"},"canonical_sha256":"7396bb01172a191328056cf9b62ab51a804654ff5f32bcbc634300b8ee682831","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:03:48.549097Z","signature_b64":"Xg89r/1U9W05L9X98VmLxmDrg2RooCNwS9pp3IWNypXsuH7ggtwaEKdAnZ60gpY6715JAeAdxlBVqQ9mU3FEDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7396bb01172a191328056cf9b62ab51a804654ff5f32bcbc634300b8ee682831","last_reissued_at":"2026-05-20T00:03:48.548245Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:03:48.548245Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.17263","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":"2026-05-20T00:03:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t//1O56UlCAtJhkPA/kW8k7qENd10QirQJwDQwVz2toz5FJJj4bhSPni3BVFvD/R7H5jGdIrf+FiLY+kRVlpAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T21:59:09.049962Z"},"content_sha256":"7fc91ceb6e1be85aa2e237337219bc849c0a6e1a9c114e16a67d3e5d7444c2a4","schema_version":"1.0","event_id":"sha256:7fc91ceb6e1be85aa2e237337219bc849c0a6e1a9c114e16a67d3e5d7444c2a4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:OOLLWAIXFIMRGKAFNT43MKVVDK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Expert Cognition Dashboard: From Learning Analytics to Cognition Intelligence in AI-Driven Education","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"Expert Cognition Dashboards let AI systems interpret learner behaviors through expert-like cognitive structures rather than raw data.","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Annie Yuan","submitted_at":"2026-05-17T05:11:31Z","abstract_excerpt":"Current AI-driven educational systems primarily rely on behavioural analytics, performance metrics, and content-level interactions to model learning. While these approaches provide useful indicators of learner activity, they are insufficient for representing the expert cognition used to interpret learner development, identify misconceptions, and make adaptive pedagogical decisions. Existing learning analytics dashboards largely visualise learner behaviour for human instructors, rather than embody expert cognition as a reasoning infrastructure for AI-native education.\n  This paper introduces th"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"ECD models expert cognition within dashboard systems, enabling learner behaviours to be interpreted through expert-like cognitive structures rather than treated as raw behavioural signals.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That expert cognition (including interpretation, misconception patterns, and learning tension) can be effectively captured and operationalized through the proposed three-layer dashboard architecture to support AI-driven adaptive interventions.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Introduces the Expert Cognition Dashboard framework that organizes learner data into multi-level cognitive structures for AI Twin-driven personalized education.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Expert Cognition Dashboards let AI systems interpret learner behaviors through expert-like cognitive structures rather than raw data.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"847ab6abdbdacea3734d30d9ef4a5ea8c919cfadf03b194db29687ac67926a4d"},"source":{"id":"2605.17263","kind":"arxiv","version":1},"verdict":{"id":"a53202ca-cc57-4366-982a-c0279a66fb48","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T23:15:03.715697Z","strongest_claim":"ECD models expert cognition within dashboard systems, enabling learner behaviours to be interpreted through expert-like cognitive structures rather than treated as raw behavioural signals.","one_line_summary":"Introduces the Expert Cognition Dashboard framework that organizes learner data into multi-level cognitive structures for AI Twin-driven personalized education.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That expert cognition (including interpretation, misconception patterns, and learning tension) can be effectively captured and operationalized through the proposed three-layer dashboard architecture to support AI-driven adaptive interventions.","pith_extraction_headline":"Expert Cognition Dashboards let AI systems interpret learner behaviors through expert-like cognitive structures rather than raw data."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.17263/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"doi_title_agreement","ran_at":"2026-05-19T23:31:20.254919Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T23:21:35.657001Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T22:01:57.845593Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T21:33:23.782878Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"e05bcad18334f79158eeb37b52dd45ecb0526b1ba2a38250122f58ab2862eede"},"references":{"count":54,"sample":[{"doi":"","year":2023,"title":"Learning and individual differences , volume=","work_id":"51602640-1b96-4224-8180-b1cf304453dd","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2010,"title":"A Review of Artificial Intelligence (AI) in Education from 2010 to 2020 , author=. Complexity , volume=. 2021 , publisher=","work_id":"486599da-6d3a-451d-8044-98174b475b65","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"Proceedings of the 2nd international conference on learning analytics and knowledge , pages=","work_id":"aa98f510-5a06-4cd9-bc7f-c116cbe232fc","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2012,"title":"International journal of technology enhanced learning , volume=","work_id":"85ee444a-27a6-48e6-a03b-789a133bc73c","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2015,"title":"Let’s not forget: Learning analytics are about learning , author=. TechTrends , volume=. 2015 , publisher=","work_id":"7061da4d-aa04-4701-a9b1-0f672d66cf26","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":54,"snapshot_sha256":"9b71bc1500f9d0b0e3742dfa1b28d6281da82c99dbfcd6a928d8b57d26539396","internal_anchors":0},"formal_canon":{"evidence_count":2,"snapshot_sha256":"b828953a143cc9b1b5424a00b46b8cdc3e8875f019e47bf0e68f6bce42524d11"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":"a53202ca-cc57-4366-982a-c0279a66fb48"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T00:03:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cGwCoWk4yisKmuzdr/aY+ZiZKr0Gq1a7B6HOVqgGTfJEZQvWcaxFz1NH82jGJQ4+b6QgPRBdPSbLusfz6DoCCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T21:59:09.050708Z"},"content_sha256":"44d2933b2ed2b24951d2428db06639a46ea67e2cad42e04cdb802c9d47c78967","schema_version":"1.0","event_id":"sha256:44d2933b2ed2b24951d2428db06639a46ea67e2cad42e04cdb802c9d47c78967"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OOLLWAIXFIMRGKAFNT43MKVVDK/bundle.json","state_url":"https://pith.science/pith/OOLLWAIXFIMRGKAFNT43MKVVDK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OOLLWAIXFIMRGKAFNT43MKVVDK/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":"2026-05-20T21:59:09Z","links":{"resolver":"https://pith.science/pith/OOLLWAIXFIMRGKAFNT43MKVVDK","bundle":"https://pith.science/pith/OOLLWAIXFIMRGKAFNT43MKVVDK/bundle.json","state":"https://pith.science/pith/OOLLWAIXFIMRGKAFNT43MKVVDK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OOLLWAIXFIMRGKAFNT43MKVVDK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:OOLLWAIXFIMRGKAFNT43MKVVDK","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":"15a9b040b6e1bfce0aea173097923b88b5cec4767ae26d05cc4365bd93e956f1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2026-05-17T05:11:31Z","title_canon_sha256":"a43e1389c7ee6d25af2cef4ab7e69080a80ddfbcdd378a64118dd33f7b8e24fe"},"schema_version":"1.0","source":{"id":"2605.17263","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.17263","created_at":"2026-05-20T00:03:48Z"},{"alias_kind":"arxiv_version","alias_value":"2605.17263v1","created_at":"2026-05-20T00:03:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17263","created_at":"2026-05-20T00:03:48Z"},{"alias_kind":"pith_short_12","alias_value":"OOLLWAIXFIMR","created_at":"2026-05-20T00:03:48Z"},{"alias_kind":"pith_short_16","alias_value":"OOLLWAIXFIMRGKAF","created_at":"2026-05-20T00:03:48Z"},{"alias_kind":"pith_short_8","alias_value":"OOLLWAIX","created_at":"2026-05-20T00:03:48Z"}],"graph_snapshots":[{"event_id":"sha256:44d2933b2ed2b24951d2428db06639a46ea67e2cad42e04cdb802c9d47c78967","target":"graph","created_at":"2026-05-20T00:03:48Z","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":"ECD models expert cognition within dashboard systems, enabling learner behaviours to be interpreted through expert-like cognitive structures rather than treated as raw behavioural signals."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That expert cognition (including interpretation, misconception patterns, and learning tension) can be effectively captured and operationalized through the proposed three-layer dashboard architecture to support AI-driven adaptive interventions."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"Introduces the Expert Cognition Dashboard framework that organizes learner data into multi-level cognitive structures for AI Twin-driven personalized education."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"Expert Cognition Dashboards let AI systems interpret learner behaviors through expert-like cognitive structures rather than raw data."}],"snapshot_sha256":"847ab6abdbdacea3734d30d9ef4a5ea8c919cfadf03b194db29687ac67926a4d"},"formal_canon":{"evidence_count":2,"snapshot_sha256":"b828953a143cc9b1b5424a00b46b8cdc3e8875f019e47bf0e68f6bce42524d11"},"integrity":{"available":true,"clean":true,"detectors_run":[{"findings_count":0,"name":"doi_title_agreement","ran_at":"2026-05-19T23:31:20.254919Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"doi_compliance","ran_at":"2026-05-19T23:21:35.657001Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T22:01:57.845593Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T21:33:23.782878Z","status":"skipped","version":"1.0.0"}],"endpoint":"/pith/2605.17263/integrity.json","findings":[],"snapshot_sha256":"e05bcad18334f79158eeb37b52dd45ecb0526b1ba2a38250122f58ab2862eede","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current AI-driven educational systems primarily rely on behavioural analytics, performance metrics, and content-level interactions to model learning. While these approaches provide useful indicators of learner activity, they are insufficient for representing the expert cognition used to interpret learner development, identify misconceptions, and make adaptive pedagogical decisions. Existing learning analytics dashboards largely visualise learner behaviour for human instructors, rather than embody expert cognition as a reasoning infrastructure for AI-native education.\n  This paper introduces th","authors_text":"Annie Yuan","cross_cats":[],"headline":"Expert Cognition Dashboards let AI systems interpret learner behaviors through expert-like cognitive structures rather than raw data.","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2026-05-17T05:11:31Z","title":"Expert Cognition Dashboard: From Learning Analytics to Cognition Intelligence in AI-Driven Education"},"references":{"count":54,"internal_anchors":0,"resolved_work":54,"sample":[{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":1,"title":"Learning and individual differences , volume=","work_id":"51602640-1b96-4224-8180-b1cf304453dd","year":2023},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":2,"title":"A Review of Artificial Intelligence (AI) in Education from 2010 to 2020 , author=. Complexity , volume=. 2021 , publisher=","work_id":"486599da-6d3a-451d-8044-98174b475b65","year":2010},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":3,"title":"Proceedings of the 2nd international conference on learning analytics and knowledge , pages=","work_id":"aa98f510-5a06-4cd9-bc7f-c116cbe232fc","year":null},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"International journal of technology enhanced learning , volume=","work_id":"85ee444a-27a6-48e6-a03b-789a133bc73c","year":2012},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"title":"Let’s not forget: Learning analytics are about learning , author=. TechTrends , volume=. 2015 , publisher=","work_id":"7061da4d-aa04-4701-a9b1-0f672d66cf26","year":2015}],"snapshot_sha256":"9b71bc1500f9d0b0e3742dfa1b28d6281da82c99dbfcd6a928d8b57d26539396"},"source":{"id":"2605.17263","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-19T23:15:03.715697Z","id":"a53202ca-cc57-4366-982a-c0279a66fb48","model_set":{"reader":"grok-4.3"},"one_line_summary":"Introduces the Expert Cognition Dashboard framework that organizes learner data into multi-level cognitive structures for AI Twin-driven personalized education.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Expert Cognition Dashboards let AI systems interpret learner behaviors through expert-like cognitive structures rather than raw data.","strongest_claim":"ECD models expert cognition within dashboard systems, enabling learner behaviours to be interpreted through expert-like cognitive structures rather than treated as raw behavioural signals.","weakest_assumption":"That expert cognition (including interpretation, misconception patterns, and learning tension) can be effectively captured and operationalized through the proposed three-layer dashboard architecture to support AI-driven adaptive interventions."}},"verdict_id":"a53202ca-cc57-4366-982a-c0279a66fb48"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:7fc91ceb6e1be85aa2e237337219bc849c0a6e1a9c114e16a67d3e5d7444c2a4","target":"record","created_at":"2026-05-20T00:03:48Z","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":"15a9b040b6e1bfce0aea173097923b88b5cec4767ae26d05cc4365bd93e956f1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2026-05-17T05:11:31Z","title_canon_sha256":"a43e1389c7ee6d25af2cef4ab7e69080a80ddfbcdd378a64118dd33f7b8e24fe"},"schema_version":"1.0","source":{"id":"2605.17263","kind":"arxiv","version":1}},"canonical_sha256":"7396bb01172a191328056cf9b62ab51a804654ff5f32bcbc634300b8ee682831","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7396bb01172a191328056cf9b62ab51a804654ff5f32bcbc634300b8ee682831","first_computed_at":"2026-05-20T00:03:48.548245Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:03:48.548245Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Xg89r/1U9W05L9X98VmLxmDrg2RooCNwS9pp3IWNypXsuH7ggtwaEKdAnZ60gpY6715JAeAdxlBVqQ9mU3FEDw==","signature_status":"signed_v1","signed_at":"2026-05-20T00:03:48.549097Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.17263","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7fc91ceb6e1be85aa2e237337219bc849c0a6e1a9c114e16a67d3e5d7444c2a4","sha256:44d2933b2ed2b24951d2428db06639a46ea67e2cad42e04cdb802c9d47c78967"],"state_sha256":"b5dfafde591a53e4768f4d6a2b20c5db71c241f91c2b4bcc0ec5825d5b088803"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UbHjnGn4HYpn91G9U3zc3y0UW4x3m0Gu7uzn/m7prZy+djW8xPSzw5jtJl07js1Xy0vEhsq5h+wQsGqhsEpjDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-20T21:59:09.055176Z","bundle_sha256":"5e11c7d389b9e3c0d2ed3de6d8296cdb8c49527fcc00d8429fcc54352faa0f72"}}