{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ON4BSUX5HMSC3OABIKVCPLOPE3","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":"b6fab414da5136c69e010ad7c6dd64a153ffc87c26b23a6fc5ceebdbbb5fcad6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-11T14:22:52Z","title_canon_sha256":"2016e3f6cef17b47837fd798485d44fce50cab0960859004ab96421753d9cadf"},"schema_version":"1.0","source":{"id":"2412.12160","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.12160","created_at":"2026-07-05T09:50:10Z"},{"alias_kind":"arxiv_version","alias_value":"2412.12160v1","created_at":"2026-07-05T09:50:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.12160","created_at":"2026-07-05T09:50:10Z"},{"alias_kind":"pith_short_12","alias_value":"ON4BSUX5HMSC","created_at":"2026-07-05T09:50:10Z"},{"alias_kind":"pith_short_16","alias_value":"ON4BSUX5HMSC3OAB","created_at":"2026-07-05T09:50:10Z"},{"alias_kind":"pith_short_8","alias_value":"ON4BSUX5","created_at":"2026-07-05T09:50:10Z"}],"graph_snapshots":[{"event_id":"sha256:9e760ee02e5e1cbf330dbf978acd39d6be01906ec8ffece7b52527a75b38e5da","target":"graph","created_at":"2026-07-05T09:50:10Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2412.12160/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Wind power forecasting plays a critical role in modern energy systems, facilitating the integration of renewable energy sources into the power grid. Accurate prediction of wind energy output is essential for managing the inherent intermittency of wind power, optimizing energy dispatch, and ensuring grid stability. This paper proposes the use of Deep Neural Network (DNN)-based predictive models that leverage climate datasets, including wind speed, atmospheric pressure, temperature, and other meteorological variables, to improve the accuracy of wind power simulations. In particular, we focus on ","authors_text":"Ali Forootani, Danial Esmaeili Aliabadi, Daniela Thraen","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-11T14:22:52Z","title":"Climate Aware Deep Neural Networks (CADNN) for Wind Power Simulation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.12160","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":"sha256:6584325c7733352f1099f2d8c84544e4453a29a94edcce54460a239bbdbdab64","target":"record","created_at":"2026-07-05T09:50:10Z","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":"b6fab414da5136c69e010ad7c6dd64a153ffc87c26b23a6fc5ceebdbbb5fcad6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-11T14:22:52Z","title_canon_sha256":"2016e3f6cef17b47837fd798485d44fce50cab0960859004ab96421753d9cadf"},"schema_version":"1.0","source":{"id":"2412.12160","kind":"arxiv","version":1}},"canonical_sha256":"73781952fd3b242db80142aa27adcf26eedeec5a86b7eaa437c4e848daedf492","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"73781952fd3b242db80142aa27adcf26eedeec5a86b7eaa437c4e848daedf492","first_computed_at":"2026-07-05T09:50:10.811305Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:50:10.811305Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hlndshjpzDGeNiP4kkTDVTkBHXQrepFetxf35zcqjhEr4nYScS7FVpIhKDSljQtUWezaYU6ZaG68vInAzG5aCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:50:10.811784Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.12160","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6584325c7733352f1099f2d8c84544e4453a29a94edcce54460a239bbdbdab64","sha256:9e760ee02e5e1cbf330dbf978acd39d6be01906ec8ffece7b52527a75b38e5da"],"state_sha256":"8db47fea7c47fff651e11a4e20712bf30652d96d249afc97f091f6e06677a3b8"}