{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:NDSXAMYLC34UKGYL4MOFQZTHZL","short_pith_number":"pith:NDSXAMYL","canonical_record":{"source":{"id":"2409.02540","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"astro-ph.SR","submitted_at":"2024-09-04T08:57:42Z","cross_cats_sorted":[],"title_canon_sha256":"7295592db19d4635d80c3085bd946a02d4dcbb8a09694f639b30b65432a38b60","abstract_canon_sha256":"3250dc3ba59e31f42ee50bfe6c9648c182f85db103dcd165879187cae56296e4"},"schema_version":"1.0"},"canonical_sha256":"68e570330b16f9451b0be31c586667caeaf6d9398426ac18eef96074cba9dc7c","source":{"kind":"arxiv","id":"2409.02540","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.02540","created_at":"2026-07-05T09:24:38Z"},{"alias_kind":"arxiv_version","alias_value":"2409.02540v2","created_at":"2026-07-05T09:24:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.02540","created_at":"2026-07-05T09:24:38Z"},{"alias_kind":"pith_short_12","alias_value":"NDSXAMYLC34U","created_at":"2026-07-05T09:24:38Z"},{"alias_kind":"pith_short_16","alias_value":"NDSXAMYLC34UKGYL","created_at":"2026-07-05T09:24:38Z"},{"alias_kind":"pith_short_8","alias_value":"NDSXAMYL","created_at":"2026-07-05T09:24:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:NDSXAMYLC34UKGYL4MOFQZTHZL","target":"record","payload":{"canonical_record":{"source":{"id":"2409.02540","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"astro-ph.SR","submitted_at":"2024-09-04T08:57:42Z","cross_cats_sorted":[],"title_canon_sha256":"7295592db19d4635d80c3085bd946a02d4dcbb8a09694f639b30b65432a38b60","abstract_canon_sha256":"3250dc3ba59e31f42ee50bfe6c9648c182f85db103dcd165879187cae56296e4"},"schema_version":"1.0"},"canonical_sha256":"68e570330b16f9451b0be31c586667caeaf6d9398426ac18eef96074cba9dc7c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:24:38.176229Z","signature_b64":"wOJ/xpSAgdFT9WmhVNJVoD/qsP74vqcdFpoJrGUkNhpC3r8iwESb2cpbKMa0SFFtca1aJwYvGBOQKlhrQr9wDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"68e570330b16f9451b0be31c586667caeaf6d9398426ac18eef96074cba9dc7c","last_reissued_at":"2026-07-05T09:24:38.175706Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:24:38.175706Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.02540","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":"2026-07-05T09:24:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VhJIARtV8NOUKgeiIbrntJwEdO5zq1wwSGliusLjlhXDxeFJizCh/Mr61q0vqjHf+21Z0sm4L0TuMV06qVOqBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:04:17.218171Z"},"content_sha256":"e57134849e9c489b2b4bb56582d0a0de2b3ded6217dcc274c33bfd6c1c80b6e2","schema_version":"1.0","event_id":"sha256:e57134849e9c489b2b4bb56582d0a0de2b3ded6217dcc274c33bfd6c1c80b6e2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:NDSXAMYLC34UKGYL4MOFQZTHZL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scalable, Advanced Machine Learning-based Approaches for Stellar Flare Identification: Application to TESS short-cadence Data and Analysis of a New Flare Catalogue","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.SR","authors_text":"Chia-Lung Lin, Daniel Apai, Mark S. Giampapa, Wing-Huen Ip","submitted_at":"2024-09-04T08:57:42Z","abstract_excerpt":"We apply multi-algorithm machine learning models to TESS 2-minute survey data from Sectors 1-72 to identify stellar flares. Models trained with Deep Neural Network, Random Forest, and XGBoost algorithms, respectively, utilized four flare light curve characteristics as input features. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics, all exceeding 94%. Validation against previously reported TESS M dwarf flare identifications showed that our models successfully recovered over 92% of the flares while detecting $\\sim2,000$ more small events, thus extending the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.02540","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2409.02540/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T09:24:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N85zwYe95dWfoVaWuNC35yhlKqLQJ9NvFsZM2cBfGg2j4aXFSZ7kRGQoFAH+XiJWlQPIoYRwoh9PThSblExFBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:04:17.218691Z"},"content_sha256":"1d61c2e20b009810e74ed6b49f521e231426dbe16d3f2a1d63ef66f999e53bb9","schema_version":"1.0","event_id":"sha256:1d61c2e20b009810e74ed6b49f521e231426dbe16d3f2a1d63ef66f999e53bb9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NDSXAMYLC34UKGYL4MOFQZTHZL/bundle.json","state_url":"https://pith.science/pith/NDSXAMYLC34UKGYL4MOFQZTHZL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NDSXAMYLC34UKGYL4MOFQZTHZL/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":"2026-08-04T15:04:17Z","links":{"resolver":"https://pith.science/pith/NDSXAMYLC34UKGYL4MOFQZTHZL","bundle":"https://pith.science/pith/NDSXAMYLC34UKGYL4MOFQZTHZL/bundle.json","state":"https://pith.science/pith/NDSXAMYLC34UKGYL4MOFQZTHZL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NDSXAMYLC34UKGYL4MOFQZTHZL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NDSXAMYLC34UKGYL4MOFQZTHZL","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":"3250dc3ba59e31f42ee50bfe6c9648c182f85db103dcd165879187cae56296e4","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"astro-ph.SR","submitted_at":"2024-09-04T08:57:42Z","title_canon_sha256":"7295592db19d4635d80c3085bd946a02d4dcbb8a09694f639b30b65432a38b60"},"schema_version":"1.0","source":{"id":"2409.02540","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.02540","created_at":"2026-07-05T09:24:38Z"},{"alias_kind":"arxiv_version","alias_value":"2409.02540v2","created_at":"2026-07-05T09:24:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.02540","created_at":"2026-07-05T09:24:38Z"},{"alias_kind":"pith_short_12","alias_value":"NDSXAMYLC34U","created_at":"2026-07-05T09:24:38Z"},{"alias_kind":"pith_short_16","alias_value":"NDSXAMYLC34UKGYL","created_at":"2026-07-05T09:24:38Z"},{"alias_kind":"pith_short_8","alias_value":"NDSXAMYL","created_at":"2026-07-05T09:24:38Z"}],"graph_snapshots":[{"event_id":"sha256:1d61c2e20b009810e74ed6b49f521e231426dbe16d3f2a1d63ef66f999e53bb9","target":"graph","created_at":"2026-07-05T09:24:38Z","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/2409.02540/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We apply multi-algorithm machine learning models to TESS 2-minute survey data from Sectors 1-72 to identify stellar flares. Models trained with Deep Neural Network, Random Forest, and XGBoost algorithms, respectively, utilized four flare light curve characteristics as input features. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics, all exceeding 94%. Validation against previously reported TESS M dwarf flare identifications showed that our models successfully recovered over 92% of the flares while detecting $\\sim2,000$ more small events, thus extending the","authors_text":"Chia-Lung Lin, Daniel Apai, Mark S. Giampapa, Wing-Huen Ip","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"astro-ph.SR","submitted_at":"2024-09-04T08:57:42Z","title":"Scalable, Advanced Machine Learning-based Approaches for Stellar Flare Identification: Application to TESS short-cadence Data and Analysis of a New Flare Catalogue"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.02540","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:e57134849e9c489b2b4bb56582d0a0de2b3ded6217dcc274c33bfd6c1c80b6e2","target":"record","created_at":"2026-07-05T09:24:38Z","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":"3250dc3ba59e31f42ee50bfe6c9648c182f85db103dcd165879187cae56296e4","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"astro-ph.SR","submitted_at":"2024-09-04T08:57:42Z","title_canon_sha256":"7295592db19d4635d80c3085bd946a02d4dcbb8a09694f639b30b65432a38b60"},"schema_version":"1.0","source":{"id":"2409.02540","kind":"arxiv","version":2}},"canonical_sha256":"68e570330b16f9451b0be31c586667caeaf6d9398426ac18eef96074cba9dc7c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"68e570330b16f9451b0be31c586667caeaf6d9398426ac18eef96074cba9dc7c","first_computed_at":"2026-07-05T09:24:38.175706Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:24:38.175706Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wOJ/xpSAgdFT9WmhVNJVoD/qsP74vqcdFpoJrGUkNhpC3r8iwESb2cpbKMa0SFFtca1aJwYvGBOQKlhrQr9wDw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:24:38.176229Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.02540","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e57134849e9c489b2b4bb56582d0a0de2b3ded6217dcc274c33bfd6c1c80b6e2","sha256:1d61c2e20b009810e74ed6b49f521e231426dbe16d3f2a1d63ef66f999e53bb9"],"state_sha256":"4ed6f5a45f22a096cb557cbd5de02f373c25f4d5a98092584ae03af00a2279a6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3tNsrVuW9Z99kvXUCHBIWstUG6DS3LYhgZLLx5SbNzycZsyzuJW69hJuoEd43oSyCgVyCnXGXO+fF1jMWXNhAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T15:04:17.222706Z","bundle_sha256":"3e3499ba7fe6bd2fb5a6d454ec70571ebd189a66afa5253659182320de037821"}}