{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:OMTREL2OP25DPP55Y3QYTPIBCH","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":"f7491628836ffa1086dab26c958847a359302df083ce078406735d0359bbc125","cross_cats_sorted":["cs.LG","cs.MS","q-bio.QM","stat.AP","stat.ME"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-08-12T07:29:29Z","title_canon_sha256":"9070ebfb8f02bec75160faec6ac030907d5487b6a58bda5711aa44be5482799e"},"schema_version":"1.0","source":{"id":"2208.06146","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.06146","created_at":"2026-07-05T06:26:41Z"},{"alias_kind":"arxiv_version","alias_value":"2208.06146v4","created_at":"2026-07-05T06:26:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.06146","created_at":"2026-07-05T06:26:41Z"},{"alias_kind":"pith_short_12","alias_value":"OMTREL2OP25D","created_at":"2026-07-05T06:26:41Z"},{"alias_kind":"pith_short_16","alias_value":"OMTREL2OP25DPP55","created_at":"2026-07-05T06:26:41Z"},{"alias_kind":"pith_short_8","alias_value":"OMTREL2O","created_at":"2026-07-05T06:26:41Z"}],"graph_snapshots":[{"event_id":"sha256:14be7efc1288505d233b019dd4cc820118b52e1e3cfbe70d0601c6a73617abf4","target":"graph","created_at":"2026-07-05T06:26:41Z","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/2208.06146/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Time series are measured and analyzed across the sciences. One method of quantifying the structure of time series is by calculating a set of summary statistics or `features', and then representing a time series in terms of its properties as a feature vector. The resulting feature space is interpretable and informative, and enables conventional statistical learning approaches, including clustering, regression, and classification, to be applied to time-series datasets. Many open-source software packages for computing sets of time-series features exist across multiple programming languages, inclu","authors_text":"Ben D. Fulcher, Trent Henderson","cross_cats":["cs.LG","cs.MS","q-bio.QM","stat.AP","stat.ME"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-08-12T07:29:29Z","title":"Feature-Based Time-Series Analysis in R using the theft Package"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.06146","kind":"arxiv","version":4},"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:e694a0381198f37713fa17f2346ed10b422300ef07fac56b68bfcfa289d364b9","target":"record","created_at":"2026-07-05T06:26:41Z","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":"f7491628836ffa1086dab26c958847a359302df083ce078406735d0359bbc125","cross_cats_sorted":["cs.LG","cs.MS","q-bio.QM","stat.AP","stat.ME"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-08-12T07:29:29Z","title_canon_sha256":"9070ebfb8f02bec75160faec6ac030907d5487b6a58bda5711aa44be5482799e"},"schema_version":"1.0","source":{"id":"2208.06146","kind":"arxiv","version":4}},"canonical_sha256":"7327122f4e7eba37bfbdc6e189bd0111e5831525f3c4569914d60b28573b747a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7327122f4e7eba37bfbdc6e189bd0111e5831525f3c4569914d60b28573b747a","first_computed_at":"2026-07-05T06:26:41.973145Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:26:41.973145Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zCJS3s8a7TxqQMcB8fJBD3H7D2sVvrZK87MiDyTNkvgLkMECEDdO0bg+ZWlK+9Udid5uvCjL517FyK2UoA9iCw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:26:41.973625Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.06146","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e694a0381198f37713fa17f2346ed10b422300ef07fac56b68bfcfa289d364b9","sha256:14be7efc1288505d233b019dd4cc820118b52e1e3cfbe70d0601c6a73617abf4"],"state_sha256":"7e529ecd245194e73a2d9bf0bf9e52eb394ed61e7d703150015c247b99c7c5f9"}