{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:RQDQNS74ZGA23AWFXFJ7UJYRWN","short_pith_number":"pith:RQDQNS74","schema_version":"1.0","canonical_sha256":"8c0706cbfcc981ad82c5b953fa2711b35b495d4b9ec2c6c5017574860eaf8b91","source":{"kind":"arxiv","id":"2102.05508","version":1},"attestation_state":"computed","paper":{"title":"Optimum Detection of Defective Elements in Non-Adaptive Group Testing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Enrico Paolini, Gianluigi Liva, Marco Chiani","submitted_at":"2021-02-10T15:52:08Z","abstract_excerpt":"We explore the problem of deriving a posteriori probabilities of being defective for the members of a population in the non-adaptive group testing framework. Both noiseless and noisy testing models are addressed. The technique, which relies of a trellis representation of the test constraints, can be applied efficiently to moderate-size populations. The complexity of the approach is discussed and numerical results on the false positive probability vs. false negative probability trade-off are presented."},"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":"2102.05508","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2021-02-10T15:52:08Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"4af04b1a8254d6e3e0a90e6cf2e4ab9c538995244de86b7893c1a14a1a7e5425","abstract_canon_sha256":"9e28f9c0604d5ae676da40e53c06e8c14a0720bf8f22d73673cd6fd400adfee0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:14:19.312140Z","signature_b64":"wpBPiG1i2zyf5Bxu1USmYWZGJcrN6B3KF6s96vFT1e5rmNXMuv65HUJhQx9OqMrBI8SrbJ9eIAe+XrNllfFdDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8c0706cbfcc981ad82c5b953fa2711b35b495d4b9ec2c6c5017574860eaf8b91","last_reissued_at":"2026-07-05T02:14:19.311808Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:14:19.311808Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Optimum Detection of Defective Elements in Non-Adaptive Group Testing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Enrico Paolini, Gianluigi Liva, Marco Chiani","submitted_at":"2021-02-10T15:52:08Z","abstract_excerpt":"We explore the problem of deriving a posteriori probabilities of being defective for the members of a population in the non-adaptive group testing framework. Both noiseless and noisy testing models are addressed. The technique, which relies of a trellis representation of the test constraints, can be applied efficiently to moderate-size populations. The complexity of the approach is discussed and numerical results on the false positive probability vs. false negative probability trade-off are presented."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.05508","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2102.05508/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":"2102.05508","created_at":"2026-07-05T02:14:19.311862+00:00"},{"alias_kind":"arxiv_version","alias_value":"2102.05508v1","created_at":"2026-07-05T02:14:19.311862+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.05508","created_at":"2026-07-05T02:14:19.311862+00:00"},{"alias_kind":"pith_short_12","alias_value":"RQDQNS74ZGA2","created_at":"2026-07-05T02:14:19.311862+00:00"},{"alias_kind":"pith_short_16","alias_value":"RQDQNS74ZGA23AWF","created_at":"2026-07-05T02:14:19.311862+00:00"},{"alias_kind":"pith_short_8","alias_value":"RQDQNS74","created_at":"2026-07-05T02:14:19.311862+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/RQDQNS74ZGA23AWFXFJ7UJYRWN","json":"https://pith.science/pith/RQDQNS74ZGA23AWFXFJ7UJYRWN.json","graph_json":"https://pith.science/api/pith-number/RQDQNS74ZGA23AWFXFJ7UJYRWN/graph.json","events_json":"https://pith.science/api/pith-number/RQDQNS74ZGA23AWFXFJ7UJYRWN/events.json","paper":"https://pith.science/paper/RQDQNS74"},"agent_actions":{"view_html":"https://pith.science/pith/RQDQNS74ZGA23AWFXFJ7UJYRWN","download_json":"https://pith.science/pith/RQDQNS74ZGA23AWFXFJ7UJYRWN.json","view_paper":"https://pith.science/paper/RQDQNS74","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2102.05508&json=true","fetch_graph":"https://pith.science/api/pith-number/RQDQNS74ZGA23AWFXFJ7UJYRWN/graph.json","fetch_events":"https://pith.science/api/pith-number/RQDQNS74ZGA23AWFXFJ7UJYRWN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RQDQNS74ZGA23AWFXFJ7UJYRWN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RQDQNS74ZGA23AWFXFJ7UJYRWN/action/storage_attestation","attest_author":"https://pith.science/pith/RQDQNS74ZGA23AWFXFJ7UJYRWN/action/author_attestation","sign_citation":"https://pith.science/pith/RQDQNS74ZGA23AWFXFJ7UJYRWN/action/citation_signature","submit_replication":"https://pith.science/pith/RQDQNS74ZGA23AWFXFJ7UJYRWN/action/replication_record"}},"created_at":"2026-07-05T02:14:19.311862+00:00","updated_at":"2026-07-05T02:14:19.311862+00:00"}