{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:AV4ZXJ3QUC5MNHBRXH2HBPP3FP","short_pith_number":"pith:AV4ZXJ3Q","canonical_record":{"source":{"id":"1708.06759","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.data-an","submitted_at":"2017-08-22T22:31:26Z","cross_cats_sorted":["math.PR"],"title_canon_sha256":"f6c753d2eb64e69c20804d3d34075f6a7b6c0628ef58466ab8437ad5d41e001a","abstract_canon_sha256":"e46ebcd87030bbb4b7b63f1ecb7bb039c9bdee01cd95e6b90c18a489f2a4f851"},"schema_version":"1.0"},"canonical_sha256":"05799ba770a0bac69c31b9f470bdfb2bf036ca15df84aeccadbcca4a08265e70","source":{"kind":"arxiv","id":"1708.06759","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.06759","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"arxiv_version","alias_value":"1708.06759v2","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.06759","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"pith_short_12","alias_value":"AV4ZXJ3QUC5M","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"AV4ZXJ3QUC5MNHBR","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"AV4ZXJ3Q","created_at":"2026-05-18T12:31:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:AV4ZXJ3QUC5MNHBRXH2HBPP3FP","target":"record","payload":{"canonical_record":{"source":{"id":"1708.06759","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.data-an","submitted_at":"2017-08-22T22:31:26Z","cross_cats_sorted":["math.PR"],"title_canon_sha256":"f6c753d2eb64e69c20804d3d34075f6a7b6c0628ef58466ab8437ad5d41e001a","abstract_canon_sha256":"e46ebcd87030bbb4b7b63f1ecb7bb039c9bdee01cd95e6b90c18a489f2a4f851"},"schema_version":"1.0"},"canonical_sha256":"05799ba770a0bac69c31b9f470bdfb2bf036ca15df84aeccadbcca4a08265e70","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:05.527021Z","signature_b64":"P2N19MUw7pjw4KSboezJdm/BYng52ATmdE5InmiqH4RazJpbaOA9/il/lDhJ+UArPvrjUxMpBkeGCsKO5favBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"05799ba770a0bac69c31b9f470bdfb2bf036ca15df84aeccadbcca4a08265e70","last_reissued_at":"2026-05-18T00:29:05.526434Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:05.526434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.06759","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":"2026-05-18T00:29:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q1u622NkvYMGvK0fkIuE7rWp8fSt1IVX+sHkXB7da7qaRuMXv/oUpZ66M9lVZAJYumPwa+shOjzrD7vTpclKCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T16:11:10.729931Z"},"content_sha256":"0fc9aad1d567e99733ab7e90fb18142c654789a9732ca9e50967611f301d847c","schema_version":"1.0","event_id":"sha256:0fc9aad1d567e99733ab7e90fb18142c654789a9732ca9e50967611f301d847c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:AV4ZXJ3QUC5MNHBRXH2HBPP3FP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Conditional Model of Wind Power Forecast Errors and Its Application in Scenario Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.PR"],"primary_cat":"physics.data-an","authors_text":"Chen Shen, Feng Liu, Zhiwen Wang","submitted_at":"2017-08-22T22:31:26Z","abstract_excerpt":"In power system operation, characterizing the stochastic nature of wind power is an important albeit challenging issue. It is well known that distributions of wind power forecast errors often exhibit significant variability with respect to different forecast values. Therefore, appropriate probabilistic models that can provide accurate information for conditional forecast error distributions are of great need. On the basis of Gaussian mixture model, this paper constructs analytical conditional distributions of forecast errors for multiple wind farms with respect to forecast values. The accuracy"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.06759","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":""},"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":"2026-05-18T00:29:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aai/pOtRHm55O6G9Tm72K4Uspsuc/sfjkbYOF/xGDqAWE1iTtxhbafoMODetMD6Tv6bsNFzPDdzncf1rcbiCCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T16:11:10.730592Z"},"content_sha256":"1b8687643d1bf53801ff3c143ac4ffe74a0c812cfe6d7d54fad138726041ee6b","schema_version":"1.0","event_id":"sha256:1b8687643d1bf53801ff3c143ac4ffe74a0c812cfe6d7d54fad138726041ee6b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AV4ZXJ3QUC5MNHBRXH2HBPP3FP/bundle.json","state_url":"https://pith.science/pith/AV4ZXJ3QUC5MNHBRXH2HBPP3FP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AV4ZXJ3QUC5MNHBRXH2HBPP3FP/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":"2026-05-25T16:11:10Z","links":{"resolver":"https://pith.science/pith/AV4ZXJ3QUC5MNHBRXH2HBPP3FP","bundle":"https://pith.science/pith/AV4ZXJ3QUC5MNHBRXH2HBPP3FP/bundle.json","state":"https://pith.science/pith/AV4ZXJ3QUC5MNHBRXH2HBPP3FP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AV4ZXJ3QUC5MNHBRXH2HBPP3FP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:AV4ZXJ3QUC5MNHBRXH2HBPP3FP","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":"e46ebcd87030bbb4b7b63f1ecb7bb039c9bdee01cd95e6b90c18a489f2a4f851","cross_cats_sorted":["math.PR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.data-an","submitted_at":"2017-08-22T22:31:26Z","title_canon_sha256":"f6c753d2eb64e69c20804d3d34075f6a7b6c0628ef58466ab8437ad5d41e001a"},"schema_version":"1.0","source":{"id":"1708.06759","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.06759","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"arxiv_version","alias_value":"1708.06759v2","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.06759","created_at":"2026-05-18T00:29:05Z"},{"alias_kind":"pith_short_12","alias_value":"AV4ZXJ3QUC5M","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"AV4ZXJ3QUC5MNHBR","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"AV4ZXJ3Q","created_at":"2026-05-18T12:31:08Z"}],"graph_snapshots":[{"event_id":"sha256:1b8687643d1bf53801ff3c143ac4ffe74a0c812cfe6d7d54fad138726041ee6b","target":"graph","created_at":"2026-05-18T00:29:05Z","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 power system operation, characterizing the stochastic nature of wind power is an important albeit challenging issue. It is well known that distributions of wind power forecast errors often exhibit significant variability with respect to different forecast values. Therefore, appropriate probabilistic models that can provide accurate information for conditional forecast error distributions are of great need. On the basis of Gaussian mixture model, this paper constructs analytical conditional distributions of forecast errors for multiple wind farms with respect to forecast values. The accuracy","authors_text":"Chen Shen, Feng Liu, Zhiwen Wang","cross_cats":["math.PR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.data-an","submitted_at":"2017-08-22T22:31:26Z","title":"A Conditional Model of Wind Power Forecast Errors and Its Application in Scenario Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.06759","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":"sha256:0fc9aad1d567e99733ab7e90fb18142c654789a9732ca9e50967611f301d847c","target":"record","created_at":"2026-05-18T00:29:05Z","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":"e46ebcd87030bbb4b7b63f1ecb7bb039c9bdee01cd95e6b90c18a489f2a4f851","cross_cats_sorted":["math.PR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.data-an","submitted_at":"2017-08-22T22:31:26Z","title_canon_sha256":"f6c753d2eb64e69c20804d3d34075f6a7b6c0628ef58466ab8437ad5d41e001a"},"schema_version":"1.0","source":{"id":"1708.06759","kind":"arxiv","version":2}},"canonical_sha256":"05799ba770a0bac69c31b9f470bdfb2bf036ca15df84aeccadbcca4a08265e70","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"05799ba770a0bac69c31b9f470bdfb2bf036ca15df84aeccadbcca4a08265e70","first_computed_at":"2026-05-18T00:29:05.526434Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:29:05.526434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"P2N19MUw7pjw4KSboezJdm/BYng52ATmdE5InmiqH4RazJpbaOA9/il/lDhJ+UArPvrjUxMpBkeGCsKO5favBA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:29:05.527021Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.06759","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0fc9aad1d567e99733ab7e90fb18142c654789a9732ca9e50967611f301d847c","sha256:1b8687643d1bf53801ff3c143ac4ffe74a0c812cfe6d7d54fad138726041ee6b"],"state_sha256":"de2e3d60ac83ad9979d56d696f39fe04b37a1b17d2d565e1909db3e9613e082e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jLbrMVtYjUdzJz/ealEYRbPQ4HXTj4TlkOb/lNkUy8ZeGYQxefWguWKPJDcbvQlIRn/mGz4EbficNCrWV9eSCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T16:11:10.734154Z","bundle_sha256":"62240a2805e40fd0ae931a133925dd87e548c063f41fb9917a8a5cf7dbe244fe"}}