{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:V2WXSCHDO7UT2W5B7WF4IWPLH7","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":"738b0c478d6cd68d80b765df0fb93520da490093a37d057d5235aa2641ec43ba","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-03T19:25:28Z","title_canon_sha256":"1ace297d2adf32e23cb711a4b46f35f2e3caa9382c2fa2404bf6c27d1e355486"},"schema_version":"1.0","source":{"id":"2211.02108","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.02108","created_at":"2026-07-05T05:22:12Z"},{"alias_kind":"arxiv_version","alias_value":"2211.02108v2","created_at":"2026-07-05T05:22:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.02108","created_at":"2026-07-05T05:22:12Z"},{"alias_kind":"pith_short_12","alias_value":"V2WXSCHDO7UT","created_at":"2026-07-05T05:22:12Z"},{"alias_kind":"pith_short_16","alias_value":"V2WXSCHDO7UT2W5B","created_at":"2026-07-05T05:22:12Z"},{"alias_kind":"pith_short_8","alias_value":"V2WXSCHD","created_at":"2026-07-05T05:22:12Z"}],"graph_snapshots":[{"event_id":"sha256:35f93efcb3b23f713dcd6f70e71be1d0b1b389dd7ed5bb6f7a87fcaeeebd7bf6","target":"graph","created_at":"2026-07-05T05:22:12Z","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/2211.02108/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Solar forecasting from ground-based sky images has shown great promise in reducing the uncertainty in solar power generation. With more and more sky image datasets open sourced in recent years, the development of accurate and reliable deep learning-based solar forecasting methods has seen a huge growth in potential. In this study, we explore three different training strategies for solar forecasting models by leveraging three heterogeneous datasets collected globally with different climate patterns. Specifically, we compare the performance of local models trained individually based on single da","authors_text":"Adam Brandt, Andea Scott, Guillaume Arbod, Joan Lasenby, Luis Martin Pomares, Quentin Paletta, Sgouris Sgouridis, Yuhao Nie","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-03T19:25:28Z","title":"Sky-image-based solar forecasting using deep learning with multi-location data: training models locally, globally or via transfer learning?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.02108","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:ac973758932856145124d202682125fc6bf79df29005bf7192bc916f24f5699e","target":"record","created_at":"2026-07-05T05:22:12Z","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":"738b0c478d6cd68d80b765df0fb93520da490093a37d057d5235aa2641ec43ba","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-03T19:25:28Z","title_canon_sha256":"1ace297d2adf32e23cb711a4b46f35f2e3caa9382c2fa2404bf6c27d1e355486"},"schema_version":"1.0","source":{"id":"2211.02108","kind":"arxiv","version":2}},"canonical_sha256":"aead7908e377e93d5ba1fd8bc459eb3fe94b8cb7cd4b4ed33c1fff1e03560590","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aead7908e377e93d5ba1fd8bc459eb3fe94b8cb7cd4b4ed33c1fff1e03560590","first_computed_at":"2026-07-05T05:22:12.158779Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:22:12.158779Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8K3qRU5LGxCoP9/kFVxNb6RpjlOZDQ6y9yBNz/dKMZY7rhP4xi+MujasjW/ytf6Le+E5gkaLMQIlPmOsGVPOBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:22:12.159293Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.02108","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ac973758932856145124d202682125fc6bf79df29005bf7192bc916f24f5699e","sha256:35f93efcb3b23f713dcd6f70e71be1d0b1b389dd7ed5bb6f7a87fcaeeebd7bf6"],"state_sha256":"2d38c01f1586422be8ef7c5bbe0a99060e1d7607478555b854fb78ce4ede3d7b"}