{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:YBVTTVWO3JJC7BHCHXYLNZDWU3","short_pith_number":"pith:YBVTTVWO","schema_version":"1.0","canonical_sha256":"c06b39d6ceda522f84e23df0b6e476a6ebc31369255d8655f9a59ff32f49fa59","source":{"kind":"arxiv","id":"1702.02656","version":1},"attestation_state":"computed","paper":{"title":"Meteor Shower Detection with Density-Based Clustering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.EP","authors_text":"Althea Moorhead, Bill Cooke, Glenn Sugar, Peter Brown","submitted_at":"2017-02-09T00:06:05Z","abstract_excerpt":"We present a new method to detect meteor showers using the Density-Based Spatial Clustering of Applications with Noise algorithm (DBSCAN; Ester et al. 1996). DBSCAN is a modern cluster detection algorithm that is well suited to the problem of extracting meteor showers from all-sky camera data because of its ability to efficiently extract clusters of different shapes and sizes from large datasets. We apply this shower detection algorithm on a dataset that contains 25,885 meteor trajectories and orbits obtained from the NASA All-Sky Fireball Network and the Southern Ontario Meteor Network (SOMN)"},"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":"1702.02656","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.EP","submitted_at":"2017-02-09T00:06:05Z","cross_cats_sorted":[],"title_canon_sha256":"4dc94372272fd2cb21d6e5154b147d3454b6d23785ae6e2125baddbc961368d4","abstract_canon_sha256":"b652da663ba2d37036189eb37af95ed592252dae2e465fcd069302c2d5595786"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:21:14.644842Z","signature_b64":"NfV2Ztjch6tGfAun9LOm3XwxlsOjI+kEjIjqdaSuo26dDxt8+MC3xHzLdyRG3zSmhQzRa35sf79GtvfKoXzsDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c06b39d6ceda522f84e23df0b6e476a6ebc31369255d8655f9a59ff32f49fa59","last_reissued_at":"2026-05-18T00:21:14.644358Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:21:14.644358Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Meteor Shower Detection with Density-Based Clustering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.EP","authors_text":"Althea Moorhead, Bill Cooke, Glenn Sugar, Peter Brown","submitted_at":"2017-02-09T00:06:05Z","abstract_excerpt":"We present a new method to detect meteor showers using the Density-Based Spatial Clustering of Applications with Noise algorithm (DBSCAN; Ester et al. 1996). DBSCAN is a modern cluster detection algorithm that is well suited to the problem of extracting meteor showers from all-sky camera data because of its ability to efficiently extract clusters of different shapes and sizes from large datasets. We apply this shower detection algorithm on a dataset that contains 25,885 meteor trajectories and orbits obtained from the NASA All-Sky Fireball Network and the Southern Ontario Meteor Network (SOMN)"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.02656","kind":"arxiv","version":1},"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":"1702.02656","created_at":"2026-05-18T00:21:14.644444+00:00"},{"alias_kind":"arxiv_version","alias_value":"1702.02656v1","created_at":"2026-05-18T00:21:14.644444+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.02656","created_at":"2026-05-18T00:21:14.644444+00:00"},{"alias_kind":"pith_short_12","alias_value":"YBVTTVWO3JJC","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_16","alias_value":"YBVTTVWO3JJC7BHC","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_8","alias_value":"YBVTTVWO","created_at":"2026-05-18T12:31:56.362134+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/YBVTTVWO3JJC7BHCHXYLNZDWU3","json":"https://pith.science/pith/YBVTTVWO3JJC7BHCHXYLNZDWU3.json","graph_json":"https://pith.science/api/pith-number/YBVTTVWO3JJC7BHCHXYLNZDWU3/graph.json","events_json":"https://pith.science/api/pith-number/YBVTTVWO3JJC7BHCHXYLNZDWU3/events.json","paper":"https://pith.science/paper/YBVTTVWO"},"agent_actions":{"view_html":"https://pith.science/pith/YBVTTVWO3JJC7BHCHXYLNZDWU3","download_json":"https://pith.science/pith/YBVTTVWO3JJC7BHCHXYLNZDWU3.json","view_paper":"https://pith.science/paper/YBVTTVWO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1702.02656&json=true","fetch_graph":"https://pith.science/api/pith-number/YBVTTVWO3JJC7BHCHXYLNZDWU3/graph.json","fetch_events":"https://pith.science/api/pith-number/YBVTTVWO3JJC7BHCHXYLNZDWU3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YBVTTVWO3JJC7BHCHXYLNZDWU3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YBVTTVWO3JJC7BHCHXYLNZDWU3/action/storage_attestation","attest_author":"https://pith.science/pith/YBVTTVWO3JJC7BHCHXYLNZDWU3/action/author_attestation","sign_citation":"https://pith.science/pith/YBVTTVWO3JJC7BHCHXYLNZDWU3/action/citation_signature","submit_replication":"https://pith.science/pith/YBVTTVWO3JJC7BHCHXYLNZDWU3/action/replication_record"}},"created_at":"2026-05-18T00:21:14.644444+00:00","updated_at":"2026-05-18T00:21:14.644444+00:00"}