{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:P2AEKIOLZUF6ICXC3EWPZIUOMS","short_pith_number":"pith:P2AEKIOL","canonical_record":{"source":{"id":"2212.03188","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.geo-ph","submitted_at":"2022-12-06T18:02:55Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"6aa9476a3d229469b7b407c818d707a49e6bd3a17e7a39fdb77f562951030eb1","abstract_canon_sha256":"6d3a0e729a6364d1ff457982f8151a0b9385c132e646b1961e34a49d0aadfdf2"},"schema_version":"1.0"},"canonical_sha256":"7e804521cbcd0be40ae2d92cfca28e64846fc8d2bc43533a6f1ab205ef1a5d24","source":{"kind":"arxiv","id":"2212.03188","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.03188","created_at":"2026-07-05T07:44:52Z"},{"alias_kind":"arxiv_version","alias_value":"2212.03188v2","created_at":"2026-07-05T07:44:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.03188","created_at":"2026-07-05T07:44:52Z"},{"alias_kind":"pith_short_12","alias_value":"P2AEKIOLZUF6","created_at":"2026-07-05T07:44:52Z"},{"alias_kind":"pith_short_16","alias_value":"P2AEKIOLZUF6ICXC","created_at":"2026-07-05T07:44:52Z"},{"alias_kind":"pith_short_8","alias_value":"P2AEKIOL","created_at":"2026-07-05T07:44:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:P2AEKIOLZUF6ICXC3EWPZIUOMS","target":"record","payload":{"canonical_record":{"source":{"id":"2212.03188","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.geo-ph","submitted_at":"2022-12-06T18:02:55Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"6aa9476a3d229469b7b407c818d707a49e6bd3a17e7a39fdb77f562951030eb1","abstract_canon_sha256":"6d3a0e729a6364d1ff457982f8151a0b9385c132e646b1961e34a49d0aadfdf2"},"schema_version":"1.0"},"canonical_sha256":"7e804521cbcd0be40ae2d92cfca28e64846fc8d2bc43533a6f1ab205ef1a5d24","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:44:52.115360Z","signature_b64":"MyyOehAqK3Z8QO1l106rTSo/8P9NhxZnARr0gJ6+t6BUR9PQvbCg3rP22GmwTTTQDD1Akleql6Q3pGTrOaK+BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7e804521cbcd0be40ae2d92cfca28e64846fc8d2bc43533a6f1ab205ef1a5d24","last_reissued_at":"2026-07-05T07:44:52.114997Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:44:52.114997Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2212.03188","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:44:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wQPAVGRW6Qz+7GAb9Mt7z+GLSZHlol9aIs1BTwGSlit7BqXpaleMLlIolPqViMgAIqaOrlmA05FZkQsyUi2DDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T10:38:05.673045Z"},"content_sha256":"c4c2b246003349e3fabe55e3d321aa19009be72e42c954d19e96f810bd51510e","schema_version":"1.0","event_id":"sha256:c4c2b246003349e3fabe55e3d321aa19009be72e42c954d19e96f810bd51510e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:P2AEKIOLZUF6ICXC3EWPZIUOMS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Unsupervised Machine Learning Approach for Ground-Motion Spectra Clustering and Selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"physics.geo-ph","authors_text":"Hao Sun, Jerome F. Hajjar, Pu Ren, R. Bailey Bond","submitted_at":"2022-12-06T18:02:55Z","abstract_excerpt":"Clustering analysis of sequence data continues to address many applications in engineering design, aided with the rapid growth of machine learning in applied science. This paper presents an unsupervised machine learning algorithm to extract defining characteristics of earthquake ground-motion spectra, also called latent features, to aid in ground-motion selection (GMS). In this context, a latent feature is a low-dimensional machine-discovered spectral characteristic learned through nonlinear relationships of a neural network autoencoder. Machine discovered latent features can be combined with "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.03188","kind":"arxiv","version":2},"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/2212.03188/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":"2026-07-05T07:44:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ttv7US9zF1QVDg9lJFrUd+FupOG6YoSM6dI3G6ok0nH9W0RK9q8BefBn6uRpJwcYPAXwvXSMxzrVraT/+ujsAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T10:38:05.673907Z"},"content_sha256":"1659619577de64f6d6091d64440843fcf6e69a7ec2e5cf28f047dfa5b0f488b5","schema_version":"1.0","event_id":"sha256:1659619577de64f6d6091d64440843fcf6e69a7ec2e5cf28f047dfa5b0f488b5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P2AEKIOLZUF6ICXC3EWPZIUOMS/bundle.json","state_url":"https://pith.science/pith/P2AEKIOLZUF6ICXC3EWPZIUOMS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P2AEKIOLZUF6ICXC3EWPZIUOMS/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":"2026-08-07T10:38:05Z","links":{"resolver":"https://pith.science/pith/P2AEKIOLZUF6ICXC3EWPZIUOMS","bundle":"https://pith.science/pith/P2AEKIOLZUF6ICXC3EWPZIUOMS/bundle.json","state":"https://pith.science/pith/P2AEKIOLZUF6ICXC3EWPZIUOMS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P2AEKIOLZUF6ICXC3EWPZIUOMS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:P2AEKIOLZUF6ICXC3EWPZIUOMS","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":"6d3a0e729a6364d1ff457982f8151a0b9385c132e646b1961e34a49d0aadfdf2","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.geo-ph","submitted_at":"2022-12-06T18:02:55Z","title_canon_sha256":"6aa9476a3d229469b7b407c818d707a49e6bd3a17e7a39fdb77f562951030eb1"},"schema_version":"1.0","source":{"id":"2212.03188","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.03188","created_at":"2026-07-05T07:44:52Z"},{"alias_kind":"arxiv_version","alias_value":"2212.03188v2","created_at":"2026-07-05T07:44:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.03188","created_at":"2026-07-05T07:44:52Z"},{"alias_kind":"pith_short_12","alias_value":"P2AEKIOLZUF6","created_at":"2026-07-05T07:44:52Z"},{"alias_kind":"pith_short_16","alias_value":"P2AEKIOLZUF6ICXC","created_at":"2026-07-05T07:44:52Z"},{"alias_kind":"pith_short_8","alias_value":"P2AEKIOL","created_at":"2026-07-05T07:44:52Z"}],"graph_snapshots":[{"event_id":"sha256:1659619577de64f6d6091d64440843fcf6e69a7ec2e5cf28f047dfa5b0f488b5","target":"graph","created_at":"2026-07-05T07:44:52Z","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/2212.03188/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Clustering analysis of sequence data continues to address many applications in engineering design, aided with the rapid growth of machine learning in applied science. This paper presents an unsupervised machine learning algorithm to extract defining characteristics of earthquake ground-motion spectra, also called latent features, to aid in ground-motion selection (GMS). In this context, a latent feature is a low-dimensional machine-discovered spectral characteristic learned through nonlinear relationships of a neural network autoencoder. Machine discovered latent features can be combined with ","authors_text":"Hao Sun, Jerome F. Hajjar, Pu Ren, R. Bailey Bond","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.geo-ph","submitted_at":"2022-12-06T18:02:55Z","title":"An Unsupervised Machine Learning Approach for Ground-Motion Spectra Clustering and Selection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.03188","kind":"arxiv","version":2},"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:c4c2b246003349e3fabe55e3d321aa19009be72e42c954d19e96f810bd51510e","target":"record","created_at":"2026-07-05T07:44:52Z","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":"6d3a0e729a6364d1ff457982f8151a0b9385c132e646b1961e34a49d0aadfdf2","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.geo-ph","submitted_at":"2022-12-06T18:02:55Z","title_canon_sha256":"6aa9476a3d229469b7b407c818d707a49e6bd3a17e7a39fdb77f562951030eb1"},"schema_version":"1.0","source":{"id":"2212.03188","kind":"arxiv","version":2}},"canonical_sha256":"7e804521cbcd0be40ae2d92cfca28e64846fc8d2bc43533a6f1ab205ef1a5d24","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7e804521cbcd0be40ae2d92cfca28e64846fc8d2bc43533a6f1ab205ef1a5d24","first_computed_at":"2026-07-05T07:44:52.114997Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:44:52.114997Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MyyOehAqK3Z8QO1l106rTSo/8P9NhxZnARr0gJ6+t6BUR9PQvbCg3rP22GmwTTTQDD1Akleql6Q3pGTrOaK+BA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:44:52.115360Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.03188","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c4c2b246003349e3fabe55e3d321aa19009be72e42c954d19e96f810bd51510e","sha256:1659619577de64f6d6091d64440843fcf6e69a7ec2e5cf28f047dfa5b0f488b5"],"state_sha256":"252eee670a1cd7b777fae26bd849fb01e23cedc2bbe4dd22eb8da4f9f7cdebe6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mqHYp8yasV5yP8rXqsozD/FkthqHXw+VDG23fGyQ6dOES7f+fgA+l/y6syyReDaYDqCal5x5/9ODvJvvNLckAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T10:38:05.679074Z","bundle_sha256":"1ac613f4e9c65107c3c5dc5b54a8c6e6c904c804547e723044e6075a564d4985"}}