{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:PEOBPCUY2D3PI7FRC26U5N2WLB","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":"13ebcbbb5fe32e453e3047d7e5dcdfc05aea0d90aee0b1a37da7d14a00e853f8","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-12T15:05:57Z","title_canon_sha256":"bcb746b9f2a638338eacc6d20465d3c1342125cb569b91283d2ebec78e1ecadc"},"schema_version":"1.0","source":{"id":"2209.05300","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.05300","created_at":"2026-07-05T04:56:29Z"},{"alias_kind":"arxiv_version","alias_value":"2209.05300v1","created_at":"2026-07-05T04:56:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.05300","created_at":"2026-07-05T04:56:29Z"},{"alias_kind":"pith_short_12","alias_value":"PEOBPCUY2D3P","created_at":"2026-07-05T04:56:29Z"},{"alias_kind":"pith_short_16","alias_value":"PEOBPCUY2D3PI7FR","created_at":"2026-07-05T04:56:29Z"},{"alias_kind":"pith_short_8","alias_value":"PEOBPCUY","created_at":"2026-07-05T04:56:29Z"}],"graph_snapshots":[{"event_id":"sha256:148c064001a14beaa4d6e76526ba452f80d42124f99d028e95a19e52d738a312","target":"graph","created_at":"2026-07-05T04:56:29Z","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/2209.05300/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper we address the application of pre-processing techniques to multi-channel time series data with varying lengths, which we refer to as the alignment problem, for downstream machine learning. The misalignment of multi-channel time series data may occur for a variety of reasons, such as missing data, varying sampling rates, or inconsistent collection times. We consider multi-channel time series data collected from the MIT SuperCloud High Performance Computing (HPC) center, where different job start times and varying run times of HPC jobs result in misaligned data. This misalignment m","authors_text":"Andrew Bowne, Andrew Prout, Charles Yee, Daniel Edelman, David Bestor, Joseph McDonald, Lindsey McEvoy, Matthew L. Weiss, Michael Jones, Siddharth Samsi, Vijay Gadepally","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-12T15:05:57Z","title":"An Evaluation of Low Overhead Time Series Preprocessing Techniques for Downstream Machine Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.05300","kind":"arxiv","version":1},"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:d0ee78c5bd890e2452cadbb397bc8055621eb6b918a4b1b0c3bee2302a271b9b","target":"record","created_at":"2026-07-05T04:56:29Z","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":"13ebcbbb5fe32e453e3047d7e5dcdfc05aea0d90aee0b1a37da7d14a00e853f8","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-12T15:05:57Z","title_canon_sha256":"bcb746b9f2a638338eacc6d20465d3c1342125cb569b91283d2ebec78e1ecadc"},"schema_version":"1.0","source":{"id":"2209.05300","kind":"arxiv","version":1}},"canonical_sha256":"791c178a98d0f6f47cb116bd4eb756585aacae75b14ad91cfe6d77e0ace3fc2e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"791c178a98d0f6f47cb116bd4eb756585aacae75b14ad91cfe6d77e0ace3fc2e","first_computed_at":"2026-07-05T04:56:29.082569Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:56:29.082569Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"P0tYd1FAwMMdHffpHCjMN4NMlBwTIDE+K7Czi7zZMfbPnskmSJFy15aqLYb9bTAPnW6sVPv8D0imS3KJLUHgBw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:56:29.083021Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.05300","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d0ee78c5bd890e2452cadbb397bc8055621eb6b918a4b1b0c3bee2302a271b9b","sha256:148c064001a14beaa4d6e76526ba452f80d42124f99d028e95a19e52d738a312"],"state_sha256":"ee4b40c0396f23b4e1769daaa6f902170ef3dc1fc8aea898a9ad9e24340dc674"}