{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:YKIVGX267LOWD7LMTIS6IRFN24","short_pith_number":"pith:YKIVGX26","schema_version":"1.0","canonical_sha256":"c291535f5efadd61fd6c9a25e444add71d9e7430a56b11dd6186d35d6d2a0488","source":{"kind":"arxiv","id":"1904.00349","version":1},"attestation_state":"computed","paper":{"title":"Efficient and error-tolerant schemes for non-adaptive complex group testing and its application in complex disease genetics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Isao Echizen, Mahdi Cheraghchi, Minoru Kuribayashi, Thach V. Bui","submitted_at":"2019-03-31T07:20:48Z","abstract_excerpt":"The goal of combinatorial group testing is to efficiently identify up to $d$ defective items in a large population of $n$ items, where $d \\ll n$. Defective items satisfy certain properties while the remaining items in the population do not. To efficiently identify defective items, a subset of items is pooled and then tested. In this work, we consider complex group testing (CmplxGT) in which a set of defective items consists of subsets of positive items (called \\textit{positive complexes}). CmplxGT is classified into two categories: classical CmplxGT (CCmplxGT) and generalized CmplxGT (GCmplxGT"},"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":"1904.00349","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2019-03-31T07:20:48Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"744fbe1e1d143aad4db9dedf6f8f76de786c473f27be10580ebf6fa05415904e","abstract_canon_sha256":"7c54c1970c1cce6ca1c4d7a7a732c4140cf9e0975d5d953432545f7ee3f3bdcd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:49:48.654812Z","signature_b64":"wQmijpiR53PP9Ie+kzvhVEZP+wGhgrjCEUp42OmvzxyO3S1eDkK0ec1ROQNABMJ/etXgICLFkN9SxdzqoQy0Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c291535f5efadd61fd6c9a25e444add71d9e7430a56b11dd6186d35d6d2a0488","last_reissued_at":"2026-05-17T23:49:48.654346Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:49:48.654346Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Efficient and error-tolerant schemes for non-adaptive complex group testing and its application in complex disease genetics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Isao Echizen, Mahdi Cheraghchi, Minoru Kuribayashi, Thach V. Bui","submitted_at":"2019-03-31T07:20:48Z","abstract_excerpt":"The goal of combinatorial group testing is to efficiently identify up to $d$ defective items in a large population of $n$ items, where $d \\ll n$. Defective items satisfy certain properties while the remaining items in the population do not. To efficiently identify defective items, a subset of items is pooled and then tested. In this work, we consider complex group testing (CmplxGT) in which a set of defective items consists of subsets of positive items (called \\textit{positive complexes}). CmplxGT is classified into two categories: classical CmplxGT (CCmplxGT) and generalized CmplxGT (GCmplxGT"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.00349","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":"1904.00349","created_at":"2026-05-17T23:49:48.654421+00:00"},{"alias_kind":"arxiv_version","alias_value":"1904.00349v1","created_at":"2026-05-17T23:49:48.654421+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.00349","created_at":"2026-05-17T23:49:48.654421+00:00"},{"alias_kind":"pith_short_12","alias_value":"YKIVGX267LOW","created_at":"2026-05-18T12:33:33.725879+00:00"},{"alias_kind":"pith_short_16","alias_value":"YKIVGX267LOWD7LM","created_at":"2026-05-18T12:33:33.725879+00:00"},{"alias_kind":"pith_short_8","alias_value":"YKIVGX26","created_at":"2026-05-18T12:33:33.725879+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/YKIVGX267LOWD7LMTIS6IRFN24","json":"https://pith.science/pith/YKIVGX267LOWD7LMTIS6IRFN24.json","graph_json":"https://pith.science/api/pith-number/YKIVGX267LOWD7LMTIS6IRFN24/graph.json","events_json":"https://pith.science/api/pith-number/YKIVGX267LOWD7LMTIS6IRFN24/events.json","paper":"https://pith.science/paper/YKIVGX26"},"agent_actions":{"view_html":"https://pith.science/pith/YKIVGX267LOWD7LMTIS6IRFN24","download_json":"https://pith.science/pith/YKIVGX267LOWD7LMTIS6IRFN24.json","view_paper":"https://pith.science/paper/YKIVGX26","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1904.00349&json=true","fetch_graph":"https://pith.science/api/pith-number/YKIVGX267LOWD7LMTIS6IRFN24/graph.json","fetch_events":"https://pith.science/api/pith-number/YKIVGX267LOWD7LMTIS6IRFN24/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YKIVGX267LOWD7LMTIS6IRFN24/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YKIVGX267LOWD7LMTIS6IRFN24/action/storage_attestation","attest_author":"https://pith.science/pith/YKIVGX267LOWD7LMTIS6IRFN24/action/author_attestation","sign_citation":"https://pith.science/pith/YKIVGX267LOWD7LMTIS6IRFN24/action/citation_signature","submit_replication":"https://pith.science/pith/YKIVGX267LOWD7LMTIS6IRFN24/action/replication_record"}},"created_at":"2026-05-17T23:49:48.654421+00:00","updated_at":"2026-05-17T23:49:48.654421+00:00"}