{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:C7SPXAKIYFCAYO7SJJIZLFU2VH","short_pith_number":"pith:C7SPXAKI","canonical_record":{"source":{"id":"1903.06700","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-15T17:52:39Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"35d9724e7a76acf248c5d6a8ce434c776c6526e815196d575baf69518414f47a","abstract_canon_sha256":"27fde3ef82af6549a0a899e27443966193c045a206ab83e4d222265524a5a100"},"schema_version":"1.0"},"canonical_sha256":"17e4fb8148c1440c3bf24a5195969aa9e38fbaa99f07c64c3ba4c6f291cb2b89","source":{"kind":"arxiv","id":"1903.06700","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.06700","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"arxiv_version","alias_value":"1903.06700v1","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.06700","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"pith_short_12","alias_value":"C7SPXAKIYFCA","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"C7SPXAKIYFCAYO7S","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"C7SPXAKI","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:C7SPXAKIYFCAYO7SJJIZLFU2VH","target":"record","payload":{"canonical_record":{"source":{"id":"1903.06700","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-15T17:52:39Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"35d9724e7a76acf248c5d6a8ce434c776c6526e815196d575baf69518414f47a","abstract_canon_sha256":"27fde3ef82af6549a0a899e27443966193c045a206ab83e4d222265524a5a100"},"schema_version":"1.0"},"canonical_sha256":"17e4fb8148c1440c3bf24a5195969aa9e38fbaa99f07c64c3ba4c6f291cb2b89","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:10.047643Z","signature_b64":"Hrh+r6VOZj9CuM2RUqS+KrlZxgiPQL876nbkhQna7/yfC/FaOJHySsNdr7h+VPs7fD8pwE/T7cPFnE81GZmFDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17e4fb8148c1440c3bf24a5195969aa9e38fbaa99f07c64c3ba4c6f291cb2b89","last_reissued_at":"2026-05-17T23:51:10.047066Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:10.047066Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.06700","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":"2026-05-17T23:51:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+Xbtlv2DIoYDkqt+KUU3J8tqQBxNEDhsT72yIXvYOS1Bb1qDa1lE5DxrIUTwVM79r4L6Pua1C8NVv2JqVbBOAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T13:21:46.686582Z"},"content_sha256":"987abbd2746fda3b99ac6490052894a6115466e364784d5a2c95d6e83025fa1c","schema_version":"1.0","event_id":"sha256:987abbd2746fda3b99ac6490052894a6115466e364784d5a2c95d6e83025fa1c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:C7SPXAKIYFCAYO7SJJIZLFU2VH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-Stage Fault Warning for Large Electric Grids Using Anomaly Detection and Machine Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Ernest Fokou\\'e, Sanjeev Raja","submitted_at":"2019-03-15T17:52:39Z","abstract_excerpt":"In the monitoring of a complex electric grid, it is of paramount importance to provide operators with early warnings of anomalies detected on the network, along with a precise classification and diagnosis of the specific fault type. In this paper, we propose a novel multi-stage early warning system prototype for electric grid fault detection, classification, subgroup discovery, and visualization. In the first stage, a computationally efficient anomaly detection method based on quartiles detects the presence of a fault in real time. In the second stage, the fault is classified into one of nine "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.06700","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-17T23:51:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h0IMEBQw2X0qJpITx7UM6gYgqDxUhhooKUtX5A9fDIJnJ5NAIslzx2+7IDtHOXz/xX50o7Pi/EHp6oZhMHQlBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T13:21:46.687249Z"},"content_sha256":"70ad62d2b566269951e1c0fff227e8d515f7b1ab77915c36a84ed55c868e8237","schema_version":"1.0","event_id":"sha256:70ad62d2b566269951e1c0fff227e8d515f7b1ab77915c36a84ed55c868e8237"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C7SPXAKIYFCAYO7SJJIZLFU2VH/bundle.json","state_url":"https://pith.science/pith/C7SPXAKIYFCAYO7SJJIZLFU2VH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C7SPXAKIYFCAYO7SJJIZLFU2VH/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":"2026-06-06T13:21:46Z","links":{"resolver":"https://pith.science/pith/C7SPXAKIYFCAYO7SJJIZLFU2VH","bundle":"https://pith.science/pith/C7SPXAKIYFCAYO7SJJIZLFU2VH/bundle.json","state":"https://pith.science/pith/C7SPXAKIYFCAYO7SJJIZLFU2VH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C7SPXAKIYFCAYO7SJJIZLFU2VH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:C7SPXAKIYFCAYO7SJJIZLFU2VH","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":"27fde3ef82af6549a0a899e27443966193c045a206ab83e4d222265524a5a100","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-15T17:52:39Z","title_canon_sha256":"35d9724e7a76acf248c5d6a8ce434c776c6526e815196d575baf69518414f47a"},"schema_version":"1.0","source":{"id":"1903.06700","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.06700","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"arxiv_version","alias_value":"1903.06700v1","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.06700","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"pith_short_12","alias_value":"C7SPXAKIYFCA","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"C7SPXAKIYFCAYO7S","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"C7SPXAKI","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:70ad62d2b566269951e1c0fff227e8d515f7b1ab77915c36a84ed55c868e8237","target":"graph","created_at":"2026-05-17T23:51:10Z","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"},"paper":{"abstract_excerpt":"In the monitoring of a complex electric grid, it is of paramount importance to provide operators with early warnings of anomalies detected on the network, along with a precise classification and diagnosis of the specific fault type. In this paper, we propose a novel multi-stage early warning system prototype for electric grid fault detection, classification, subgroup discovery, and visualization. In the first stage, a computationally efficient anomaly detection method based on quartiles detects the presence of a fault in real time. In the second stage, the fault is classified into one of nine ","authors_text":"Ernest Fokou\\'e, Sanjeev Raja","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-15T17:52:39Z","title":"Multi-Stage Fault Warning for Large Electric Grids Using Anomaly Detection and Machine Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.06700","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":"sha256:987abbd2746fda3b99ac6490052894a6115466e364784d5a2c95d6e83025fa1c","target":"record","created_at":"2026-05-17T23:51:10Z","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":"27fde3ef82af6549a0a899e27443966193c045a206ab83e4d222265524a5a100","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-15T17:52:39Z","title_canon_sha256":"35d9724e7a76acf248c5d6a8ce434c776c6526e815196d575baf69518414f47a"},"schema_version":"1.0","source":{"id":"1903.06700","kind":"arxiv","version":1}},"canonical_sha256":"17e4fb8148c1440c3bf24a5195969aa9e38fbaa99f07c64c3ba4c6f291cb2b89","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"17e4fb8148c1440c3bf24a5195969aa9e38fbaa99f07c64c3ba4c6f291cb2b89","first_computed_at":"2026-05-17T23:51:10.047066Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:51:10.047066Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Hrh+r6VOZj9CuM2RUqS+KrlZxgiPQL876nbkhQna7/yfC/FaOJHySsNdr7h+VPs7fD8pwE/T7cPFnE81GZmFDg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:51:10.047643Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.06700","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:987abbd2746fda3b99ac6490052894a6115466e364784d5a2c95d6e83025fa1c","sha256:70ad62d2b566269951e1c0fff227e8d515f7b1ab77915c36a84ed55c868e8237"],"state_sha256":"9df661aeee115864e1f15a333fe2766589bc80c3897cabdc14c49a174ff3f65c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OJrfmSOW4MKKZUYvaTlfsSjgNOLaj4G/oI8H2FiLmZBRD8zTFQOKLd4pM4/M7DWoMIce3LsNzNyYRxz8WcoUBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T13:21:46.690809Z","bundle_sha256":"86236bc2f0fff69faedca3544e949644ad20172430efbd79fb5bf8946b7eeb86"}}