{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:USGQQSFKLWHLGV7HWZASBQVWOW","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":"b3beaee40c9015d3f5ca190d8d799513649155cc6b683f94e1f9cc6577b5a028","cross_cats_sorted":["cs.SD","eess.AS","stat.CO"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"stat.AP","submitted_at":"2025-06-27T05:21:20Z","title_canon_sha256":"14551ff75ce4669660c3d310cb83f6a6b08ae0c1ed8f198b609a3f1d3bbbb98c"},"schema_version":"1.0","source":{"id":"2506.21921","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.21921","created_at":"2026-07-05T11:28:18Z"},{"alias_kind":"arxiv_version","alias_value":"2506.21921v1","created_at":"2026-07-05T11:28:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.21921","created_at":"2026-07-05T11:28:18Z"},{"alias_kind":"pith_short_12","alias_value":"USGQQSFKLWHL","created_at":"2026-07-05T11:28:18Z"},{"alias_kind":"pith_short_16","alias_value":"USGQQSFKLWHLGV7H","created_at":"2026-07-05T11:28:18Z"},{"alias_kind":"pith_short_8","alias_value":"USGQQSFK","created_at":"2026-07-05T11:28:18Z"}],"graph_snapshots":[{"event_id":"sha256:673ebcdef018561201766720172db822a7b5353d5e5f015ca78ebbec502e96aa","target":"graph","created_at":"2026-07-05T11:28:18Z","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/2506.21921/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Anomaly detection is the task of identifying rarely occurring (i.e. anormal or anomalous) samples that differ from almost all other samples in a dataset. As the patterns of anormal samples are usually not known a priori, this task is highly challenging. Consequently, anomaly detection lies between semi- and unsupervised learning. The detection of anomalies in sound data, often called 'ASD' (Anomalous Sound Detection), is a sub-field that deals with the identification of new and yet unknown effects in acoustic recordings. It is of great importance for various applications in Industry 4.0. Here,","authors_text":"Georg Schneider, Markus Pauly, Nicolas Thewes, Patrick Trampert, Philipp Steinhauer","cross_cats":["cs.SD","eess.AS","stat.CO"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"stat.AP","submitted_at":"2025-06-27T05:21:20Z","title":"Explainable anomaly detection for sound spectrograms using pooling statistics with quantile differences"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.21921","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":"sha256:1478e196b5ab50df6d969dd0ecc0d95f70121be2bf7aa90d5c5cd5f8a93d0fd8","target":"record","created_at":"2026-07-05T11:28:18Z","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":"b3beaee40c9015d3f5ca190d8d799513649155cc6b683f94e1f9cc6577b5a028","cross_cats_sorted":["cs.SD","eess.AS","stat.CO"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"stat.AP","submitted_at":"2025-06-27T05:21:20Z","title_canon_sha256":"14551ff75ce4669660c3d310cb83f6a6b08ae0c1ed8f198b609a3f1d3bbbb98c"},"schema_version":"1.0","source":{"id":"2506.21921","kind":"arxiv","version":1}},"canonical_sha256":"a48d0848aa5d8eb357e7b64120c2b67581fa41bc5412a655c43cfacebbecf5cc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a48d0848aa5d8eb357e7b64120c2b67581fa41bc5412a655c43cfacebbecf5cc","first_computed_at":"2026-07-05T11:28:18.430765Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:28:18.430765Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xWomhGkhyw+mES3XPPnyBByWlsC+5Y7akyT0EMSfvIW7BGrMj/p6vXLsNWzAVYaJxdg4P7d6MuER/KHMedqdCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:28:18.431244Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.21921","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1478e196b5ab50df6d969dd0ecc0d95f70121be2bf7aa90d5c5cd5f8a93d0fd8","sha256:673ebcdef018561201766720172db822a7b5353d5e5f015ca78ebbec502e96aa"],"state_sha256":"a2825da84a733b2e5988dde9b85160c2d38f309ba2a97088b0ac4f5257d16149"}