{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:X3QV7VFJPSL4AB3RNGSUZVHZ37","short_pith_number":"pith:X3QV7VFJ","schema_version":"1.0","canonical_sha256":"bee15fd4a97c97c0077169a54cd4f9dfca38ff883e21989c8928937e9752cced","source":{"kind":"arxiv","id":"1904.12288","version":4},"attestation_state":"computed","paper":{"title":"Application of Machine Learning to the Particle Identification of GAPS","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.IM","authors_text":"Hideyuki Fuke, Takuya Wada, Tetsuya Yoshida, Yuki Shimizu","submitted_at":"2019-04-28T09:40:01Z","abstract_excerpt":"GAPS is an international balloon-borne project that contributes to solving the dark-matter mystery through a highly sensitive survey of cosmic-ray antiparticles, especially undiscovered antideuterons. To achieve a sufficient sensitivity to rare antideuterons, a novel particle identification method based on exotic atom capture and decay has been developed. In parallel to utilizing this unique event signature in a conventional likelihood-based event identification scheme, we have begun investigating a complementary approach using a machine learning technique. In this new approach, a deep-learnin"},"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":"1904.12288","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.IM","submitted_at":"2019-04-28T09:40:01Z","cross_cats_sorted":[],"title_canon_sha256":"5ac7b2558345c0dfbdb1eda0465ebfa95ff8925c8967d76f71d2b723b2b43cda","abstract_canon_sha256":"ca74dfbf727641fca6d5dfe684259552587defec0f6309bdb85e3fa6cb38b96a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:03:56.160948Z","signature_b64":"UeIWv2sBvDjvswzRR4hWZazunI9+/F71UEf01/Ui/Tf1mm2H5UjApMMEQqdoVNZvPgSswQrLeLnbxPn4vt5ZCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bee15fd4a97c97c0077169a54cd4f9dfca38ff883e21989c8928937e9752cced","last_reissued_at":"2026-07-05T00:03:56.160484Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:03:56.160484Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Application of Machine Learning to the Particle Identification of GAPS","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.IM","authors_text":"Hideyuki Fuke, Takuya Wada, Tetsuya Yoshida, Yuki Shimizu","submitted_at":"2019-04-28T09:40:01Z","abstract_excerpt":"GAPS is an international balloon-borne project that contributes to solving the dark-matter mystery through a highly sensitive survey of cosmic-ray antiparticles, especially undiscovered antideuterons. To achieve a sufficient sensitivity to rare antideuterons, a novel particle identification method based on exotic atom capture and decay has been developed. In parallel to utilizing this unique event signature in a conventional likelihood-based event identification scheme, we have begun investigating a complementary approach using a machine learning technique. In this new approach, a deep-learnin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.12288","kind":"arxiv","version":4},"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/1904.12288/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":"1904.12288","created_at":"2026-07-05T00:03:56.160543+00:00"},{"alias_kind":"arxiv_version","alias_value":"1904.12288v4","created_at":"2026-07-05T00:03:56.160543+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.12288","created_at":"2026-07-05T00:03:56.160543+00:00"},{"alias_kind":"pith_short_12","alias_value":"X3QV7VFJPSL4","created_at":"2026-07-05T00:03:56.160543+00:00"},{"alias_kind":"pith_short_16","alias_value":"X3QV7VFJPSL4AB3R","created_at":"2026-07-05T00:03:56.160543+00:00"},{"alias_kind":"pith_short_8","alias_value":"X3QV7VFJ","created_at":"2026-07-05T00:03:56.160543+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/X3QV7VFJPSL4AB3RNGSUZVHZ37","json":"https://pith.science/pith/X3QV7VFJPSL4AB3RNGSUZVHZ37.json","graph_json":"https://pith.science/api/pith-number/X3QV7VFJPSL4AB3RNGSUZVHZ37/graph.json","events_json":"https://pith.science/api/pith-number/X3QV7VFJPSL4AB3RNGSUZVHZ37/events.json","paper":"https://pith.science/paper/X3QV7VFJ"},"agent_actions":{"view_html":"https://pith.science/pith/X3QV7VFJPSL4AB3RNGSUZVHZ37","download_json":"https://pith.science/pith/X3QV7VFJPSL4AB3RNGSUZVHZ37.json","view_paper":"https://pith.science/paper/X3QV7VFJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1904.12288&json=true","fetch_graph":"https://pith.science/api/pith-number/X3QV7VFJPSL4AB3RNGSUZVHZ37/graph.json","fetch_events":"https://pith.science/api/pith-number/X3QV7VFJPSL4AB3RNGSUZVHZ37/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/X3QV7VFJPSL4AB3RNGSUZVHZ37/action/timestamp_anchor","attest_storage":"https://pith.science/pith/X3QV7VFJPSL4AB3RNGSUZVHZ37/action/storage_attestation","attest_author":"https://pith.science/pith/X3QV7VFJPSL4AB3RNGSUZVHZ37/action/author_attestation","sign_citation":"https://pith.science/pith/X3QV7VFJPSL4AB3RNGSUZVHZ37/action/citation_signature","submit_replication":"https://pith.science/pith/X3QV7VFJPSL4AB3RNGSUZVHZ37/action/replication_record"}},"created_at":"2026-07-05T00:03:56.160543+00:00","updated_at":"2026-07-05T00:03:56.160543+00:00"}