{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4DSLE53MKHVVVNMLJZBJBXOAVL","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":"02d3a4250d2bafb3a003fc95689329cc75fc7ae79bcad8ac83ffb2fdffe217e9","cross_cats_sorted":["astro-ph.HE","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"astro-ph.IM","submitted_at":"2025-03-06T00:09:01Z","title_canon_sha256":"28fe6a47a16f083922dba44b52fd80e57c5773577897147277575b51f0ae00f7"},"schema_version":"1.0","source":{"id":"2503.03982","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.03982","created_at":"2026-07-05T10:43:26Z"},{"alias_kind":"arxiv_version","alias_value":"2503.03982v1","created_at":"2026-07-05T10:43:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.03982","created_at":"2026-07-05T10:43:26Z"},{"alias_kind":"pith_short_12","alias_value":"4DSLE53MKHVV","created_at":"2026-07-05T10:43:26Z"},{"alias_kind":"pith_short_16","alias_value":"4DSLE53MKHVVVNML","created_at":"2026-07-05T10:43:26Z"},{"alias_kind":"pith_short_8","alias_value":"4DSLE53M","created_at":"2026-07-05T10:43:26Z"}],"graph_snapshots":[{"event_id":"sha256:bc69bd219737502a544718f50c56ba588616915dc6293453f00d40b380c6589b","target":"graph","created_at":"2026-07-05T10:43:26Z","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/2503.03982/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Modern Imaging Atmospheric Cherenkov Telescopes (IACTs) generate a huge amount of data that must be classified automatically, ideally in real time. Currently, machine learning-based solutions are increasingly being used to solve classification problems. However, these classifiers require proper training data sets to work correctly. The problem with training neural networks on real IACT data is that these data need to be pre-labeled, whereas such labeling is difficult and its results are estimates. In addition, the distribution of incoming events is highly imbalanced. Firstly, there is an imbal","authors_text":"A. A. Vlaskina, A. P. Kryukov, D. P. Zhurov, E. B. Postnikov, E. O. Gres, P. A. Volchugov, S. P. Polyakov, Yu. Yu. Dubenskaya","cross_cats":["astro-ph.HE","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"astro-ph.IM","submitted_at":"2025-03-06T00:09:01Z","title":"Image Data Augmentation for the TAIGA-IACT Experiment with Conditional Generative Adversarial Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.03982","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:d2c5798c9b76aa4c123197e81c6ac1ce3e4940a6ddb493718f5626090af1a923","target":"record","created_at":"2026-07-05T10:43:26Z","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":"02d3a4250d2bafb3a003fc95689329cc75fc7ae79bcad8ac83ffb2fdffe217e9","cross_cats_sorted":["astro-ph.HE","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"astro-ph.IM","submitted_at":"2025-03-06T00:09:01Z","title_canon_sha256":"28fe6a47a16f083922dba44b52fd80e57c5773577897147277575b51f0ae00f7"},"schema_version":"1.0","source":{"id":"2503.03982","kind":"arxiv","version":1}},"canonical_sha256":"e0e4b2776c51eb5ab58b4e4290ddc0aaf641a95e2bee02c0a4a5d4cda5132200","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e0e4b2776c51eb5ab58b4e4290ddc0aaf641a95e2bee02c0a4a5d4cda5132200","first_computed_at":"2026-07-05T10:43:26.618794Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:43:26.618794Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"p1aDIKKgpdJkS1Z9/l/sJDVpv8KpA0cm3Im5UPRbIvS6atShiEtimYUEVzV2SOxCKNBNXm6ysc/Rr0xSNZCEDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:43:26.619350Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.03982","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d2c5798c9b76aa4c123197e81c6ac1ce3e4940a6ddb493718f5626090af1a923","sha256:bc69bd219737502a544718f50c56ba588616915dc6293453f00d40b380c6589b"],"state_sha256":"a637d1a05ae4b580e77f8ae4045e2b7800570452981e4ce1277034bfee2b04f9"}