{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:LHATIE2N7PEPMQXVT4UFOEQ5Z5","short_pith_number":"pith:LHATIE2N","schema_version":"1.0","canonical_sha256":"59c134134dfbc8f642f59f2857121dcf5254ccc08439af91aee69d70eb94407c","source":{"kind":"arxiv","id":"2111.10009","version":2},"attestation_state":"computed","paper":{"title":"ExoMiner: A Highly Accurate and Explainable Deep Learning Classifier that Validates 301 New Exoplanets","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM","cs.LG"],"primary_cat":"astro-ph.EP","authors_text":"Douglas A. Caldwell, Hamed Valizadegan, Jeffrey Smith, Jon M. Jenkins, Joseph D. Twicken, Kaylie Hausknecht, Laurent S. Wilkens, Miguel Martinho, Nikash Walia, Nikunj C. Oza, Noa Y. Lubin, Pedro C. Gerum, Stephen T. Bryson","submitted_at":"2021-11-19T02:22:34Z","abstract_excerpt":"The kepler and TESS missions have generated over 100,000 potential transit signals that must be processed in order to create a catalog of planet candidates. During the last few years, there has been a growing interest in using machine learning to analyze these data in search of new exoplanets. Different from the existing machine learning works, ExoMiner, the proposed deep learning classifier in this work, mimics how domain experts examine diagnostic tests to vet a transit signal. ExoMiner is a highly accurate, explainable, and robust classifier that 1) allows us to validate 301 new exoplanets "},"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":"2111.10009","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.EP","submitted_at":"2021-11-19T02:22:34Z","cross_cats_sorted":["astro-ph.IM","cs.LG"],"title_canon_sha256":"34ea8a8ce886a40bd0b926b5cc69df8f2a305695e23f7bb5061ef365f5c183fa","abstract_canon_sha256":"aa2d1be272ce56a032b056cf73c9d0767ecd3cdb75ad712da53a08c0c9109d4b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:58:57.826865Z","signature_b64":"LdWMSFLo/RX4kZ9m4d0YQPxZSbmZSzPiJzo9RP6NU/Yl4qYMNd/6qz80vvzWvFlmJwhcDFbNQXp+V3a3SW4rCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59c134134dfbc8f642f59f2857121dcf5254ccc08439af91aee69d70eb94407c","last_reissued_at":"2026-07-05T03:58:57.826207Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:58:57.826207Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ExoMiner: A Highly Accurate and Explainable Deep Learning Classifier that Validates 301 New Exoplanets","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM","cs.LG"],"primary_cat":"astro-ph.EP","authors_text":"Douglas A. Caldwell, Hamed Valizadegan, Jeffrey Smith, Jon M. Jenkins, Joseph D. Twicken, Kaylie Hausknecht, Laurent S. Wilkens, Miguel Martinho, Nikash Walia, Nikunj C. Oza, Noa Y. Lubin, Pedro C. Gerum, Stephen T. Bryson","submitted_at":"2021-11-19T02:22:34Z","abstract_excerpt":"The kepler and TESS missions have generated over 100,000 potential transit signals that must be processed in order to create a catalog of planet candidates. During the last few years, there has been a growing interest in using machine learning to analyze these data in search of new exoplanets. Different from the existing machine learning works, ExoMiner, the proposed deep learning classifier in this work, mimics how domain experts examine diagnostic tests to vet a transit signal. ExoMiner is a highly accurate, explainable, and robust classifier that 1) allows us to validate 301 new exoplanets "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.10009","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/2111.10009/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2111.10009","created_at":"2026-07-05T03:58:57.826279+00:00"},{"alias_kind":"arxiv_version","alias_value":"2111.10009v2","created_at":"2026-07-05T03:58:57.826279+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.10009","created_at":"2026-07-05T03:58:57.826279+00:00"},{"alias_kind":"pith_short_12","alias_value":"LHATIE2N7PEP","created_at":"2026-07-05T03:58:57.826279+00:00"},{"alias_kind":"pith_short_16","alias_value":"LHATIE2N7PEPMQXV","created_at":"2026-07-05T03:58:57.826279+00:00"},{"alias_kind":"pith_short_8","alias_value":"LHATIE2N","created_at":"2026-07-05T03:58:57.826279+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2509.06478","citing_title":"Selected Results on Variable Stars Observed by TESS","ref_index":30,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/LHATIE2N7PEPMQXVT4UFOEQ5Z5","json":"https://pith.science/pith/LHATIE2N7PEPMQXVT4UFOEQ5Z5.json","graph_json":"https://pith.science/api/pith-number/LHATIE2N7PEPMQXVT4UFOEQ5Z5/graph.json","events_json":"https://pith.science/api/pith-number/LHATIE2N7PEPMQXVT4UFOEQ5Z5/events.json","paper":"https://pith.science/paper/LHATIE2N"},"agent_actions":{"view_html":"https://pith.science/pith/LHATIE2N7PEPMQXVT4UFOEQ5Z5","download_json":"https://pith.science/pith/LHATIE2N7PEPMQXVT4UFOEQ5Z5.json","view_paper":"https://pith.science/paper/LHATIE2N","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2111.10009&json=true","fetch_graph":"https://pith.science/api/pith-number/LHATIE2N7PEPMQXVT4UFOEQ5Z5/graph.json","fetch_events":"https://pith.science/api/pith-number/LHATIE2N7PEPMQXVT4UFOEQ5Z5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LHATIE2N7PEPMQXVT4UFOEQ5Z5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LHATIE2N7PEPMQXVT4UFOEQ5Z5/action/storage_attestation","attest_author":"https://pith.science/pith/LHATIE2N7PEPMQXVT4UFOEQ5Z5/action/author_attestation","sign_citation":"https://pith.science/pith/LHATIE2N7PEPMQXVT4UFOEQ5Z5/action/citation_signature","submit_replication":"https://pith.science/pith/LHATIE2N7PEPMQXVT4UFOEQ5Z5/action/replication_record"}},"created_at":"2026-07-05T03:58:57.826279+00:00","updated_at":"2026-07-05T03:58:57.826279+00:00"}