{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:F475QNGHKUXUJDO6UEM57YNIVJ","short_pith_number":"pith:F475QNGH","schema_version":"1.0","canonical_sha256":"2f3fd834c7552f448ddea119dfe1a8aa526b583cfc5935b996bc5d12588a3724","source":{"kind":"arxiv","id":"1705.06405","version":3},"attestation_state":"computed","paper":{"title":"Deep Learning Classification in Asteroseismology","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.IM"],"primary_cat":"astro-ph.SR","authors_text":"Dennis Stello, Jie Yu, Marc Hon","submitted_at":"2017-05-18T03:17:34Z","abstract_excerpt":"In the power spectra of oscillating red giants, there are visually distinct features defining stars ascending the red giant branch from those that have commenced helium core burning. We train a one-dimensional convolutional neural network by supervised learning to automatically learn these visual features from images of folded oscillation spectra. By training and testing on \\textit{Kepler} red giants, we achieve an accuracy of up to 99\\% in separating helium-burning red giants from those ascending the red giant branch. The convolutional neural network additionally shows capability in accuratel"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1705.06405","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.SR","submitted_at":"2017-05-18T03:17:34Z","cross_cats_sorted":["astro-ph.IM"],"title_canon_sha256":"af78eb2ca262b6d6c17bf0ef0cab18fecc2428f4c3424ecab8ccedd055cc1cf7","abstract_canon_sha256":"028bee78627538aaa40b5fbb8f394018d815e0452f2413b98420b6f17ed19ff1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:42:12.002383Z","signature_b64":"Ye1t0DMW884r5niUs2FSydpSXAZ1ZndwSe5rwzIU5YSfwe15uZvMR0XAKJEvRnRHjb0V5fouJdqzmt/lBdLHCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2f3fd834c7552f448ddea119dfe1a8aa526b583cfc5935b996bc5d12588a3724","last_reissued_at":"2026-05-18T00:42:12.001753Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:42:12.001753Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Deep Learning Classification in Asteroseismology","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.IM"],"primary_cat":"astro-ph.SR","authors_text":"Dennis Stello, Jie Yu, Marc Hon","submitted_at":"2017-05-18T03:17:34Z","abstract_excerpt":"In the power spectra of oscillating red giants, there are visually distinct features defining stars ascending the red giant branch from those that have commenced helium core burning. We train a one-dimensional convolutional neural network by supervised learning to automatically learn these visual features from images of folded oscillation spectra. By training and testing on \\textit{Kepler} red giants, we achieve an accuracy of up to 99\\% in separating helium-burning red giants from those ascending the red giant branch. The convolutional neural network additionally shows capability in accuratel"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.06405","kind":"arxiv","version":3},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1705.06405","created_at":"2026-05-18T00:42:12.001844+00:00"},{"alias_kind":"arxiv_version","alias_value":"1705.06405v3","created_at":"2026-05-18T00:42:12.001844+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.06405","created_at":"2026-05-18T00:42:12.001844+00:00"},{"alias_kind":"pith_short_12","alias_value":"F475QNGHKUXU","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_16","alias_value":"F475QNGHKUXUJDO6","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_8","alias_value":"F475QNGH","created_at":"2026-05-18T12:31:15.632608+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/F475QNGHKUXUJDO6UEM57YNIVJ","json":"https://pith.science/pith/F475QNGHKUXUJDO6UEM57YNIVJ.json","graph_json":"https://pith.science/api/pith-number/F475QNGHKUXUJDO6UEM57YNIVJ/graph.json","events_json":"https://pith.science/api/pith-number/F475QNGHKUXUJDO6UEM57YNIVJ/events.json","paper":"https://pith.science/paper/F475QNGH"},"agent_actions":{"view_html":"https://pith.science/pith/F475QNGHKUXUJDO6UEM57YNIVJ","download_json":"https://pith.science/pith/F475QNGHKUXUJDO6UEM57YNIVJ.json","view_paper":"https://pith.science/paper/F475QNGH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1705.06405&json=true","fetch_graph":"https://pith.science/api/pith-number/F475QNGHKUXUJDO6UEM57YNIVJ/graph.json","fetch_events":"https://pith.science/api/pith-number/F475QNGHKUXUJDO6UEM57YNIVJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/F475QNGHKUXUJDO6UEM57YNIVJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/F475QNGHKUXUJDO6UEM57YNIVJ/action/storage_attestation","attest_author":"https://pith.science/pith/F475QNGHKUXUJDO6UEM57YNIVJ/action/author_attestation","sign_citation":"https://pith.science/pith/F475QNGHKUXUJDO6UEM57YNIVJ/action/citation_signature","submit_replication":"https://pith.science/pith/F475QNGHKUXUJDO6UEM57YNIVJ/action/replication_record"}},"created_at":"2026-05-18T00:42:12.001844+00:00","updated_at":"2026-05-18T00:42:12.001844+00:00"}