{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:2Z2W7WLXFFPNTMLQZI2GK5AHVM","short_pith_number":"pith:2Z2W7WLX","canonical_record":{"source":{"id":"1602.03969","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-02-12T07:34:33Z","cross_cats_sorted":["math.IT","math.ST","stat.TH"],"title_canon_sha256":"9a0f523ad2b0b056bae42ccc85f38c9373551ed50a102a04fed092fc0df47f47","abstract_canon_sha256":"3e8cef3ac6beceb35d3575d4bea652dfbf0d8cd5f6fb5dea34c912c6534e0f56"},"schema_version":"1.0"},"canonical_sha256":"d6756fd977295ed9b170ca34657407ab3961fbe3428ad7a6ac5f024bbd21b0ac","source":{"kind":"arxiv","id":"1602.03969","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.03969","created_at":"2026-05-18T01:20:55Z"},{"alias_kind":"arxiv_version","alias_value":"1602.03969v1","created_at":"2026-05-18T01:20:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.03969","created_at":"2026-05-18T01:20:55Z"},{"alias_kind":"pith_short_12","alias_value":"2Z2W7WLXFFPN","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_16","alias_value":"2Z2W7WLXFFPNTMLQ","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_8","alias_value":"2Z2W7WLX","created_at":"2026-05-18T12:29:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:2Z2W7WLXFFPNTMLQZI2GK5AHVM","target":"record","payload":{"canonical_record":{"source":{"id":"1602.03969","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-02-12T07:34:33Z","cross_cats_sorted":["math.IT","math.ST","stat.TH"],"title_canon_sha256":"9a0f523ad2b0b056bae42ccc85f38c9373551ed50a102a04fed092fc0df47f47","abstract_canon_sha256":"3e8cef3ac6beceb35d3575d4bea652dfbf0d8cd5f6fb5dea34c912c6534e0f56"},"schema_version":"1.0"},"canonical_sha256":"d6756fd977295ed9b170ca34657407ab3961fbe3428ad7a6ac5f024bbd21b0ac","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:20:55.030664Z","signature_b64":"ZkDOLVD31ppZSny8nAsZ2o35qkWtbiMGU0WfFis+/y8eZz/5iBrXP3uo4MG8V34Xz4hrpz2D/TOjQM0DTgDECA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6756fd977295ed9b170ca34657407ab3961fbe3428ad7a6ac5f024bbd21b0ac","last_reissued_at":"2026-05-18T01:20:55.029809Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:20:55.029809Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1602.03969","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:20:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nfAh9dNJRgKjcWuRC0eyGyZKERgJWrptPeBUjTHmIwcDd9QXa8rQXlkvZy07jj1OGHHaC09rukkeBglGppOUAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T05:02:55.370807Z"},"content_sha256":"f300fb0e2ff466bb500e1693db7efed4ce8a0c795b3ff904fb8f408a1e07c93c","schema_version":"1.0","event_id":"sha256:f300fb0e2ff466bb500e1693db7efed4ce8a0c795b3ff904fb8f408a1e07c93c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:2Z2W7WLXFFPNTMLQZI2GK5AHVM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Opportunistic Detection Rules: Finite and Asymptotic Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT","math.ST","stat.TH"],"primary_cat":"cs.IT","authors_text":"George V. Moustakides, H. Vincent Poor, Wenyi Zhang","submitted_at":"2016-02-12T07:34:33Z","abstract_excerpt":"Opportunistic detection rules (ODRs) are variants of fixed-sample-size detection rules in which the statistician is allowed to make an early decision on the alternative hypothesis opportunistically based on the sequentially observed samples. From a sequential decision perspective, ODRs are also mixtures of one-sided and truncated sequential detection rules. Several results regarding ODRs are established in this paper. In the finite regime, the maximum sample size is modeled either as a fixed finite number, or a geometric random variable with a fixed finite mean. For both cases, the correspondi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.03969","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:20:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nUkmMAosNnVoyEDp4Rh+tJpJuZydpnubhbDRmdW4P3ZhYPOE6Qk67cfRgkxdhOI7IKZTpWnKIdfuVxyNXwYFBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T05:02:55.371141Z"},"content_sha256":"b0cddfdbbcf942e1cd05fb048a94e00c72785c1c0faaf950d843d29a968c89ed","schema_version":"1.0","event_id":"sha256:b0cddfdbbcf942e1cd05fb048a94e00c72785c1c0faaf950d843d29a968c89ed"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2Z2W7WLXFFPNTMLQZI2GK5AHVM/bundle.json","state_url":"https://pith.science/pith/2Z2W7WLXFFPNTMLQZI2GK5AHVM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2Z2W7WLXFFPNTMLQZI2GK5AHVM/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-02T05:02:55Z","links":{"resolver":"https://pith.science/pith/2Z2W7WLXFFPNTMLQZI2GK5AHVM","bundle":"https://pith.science/pith/2Z2W7WLXFFPNTMLQZI2GK5AHVM/bundle.json","state":"https://pith.science/pith/2Z2W7WLXFFPNTMLQZI2GK5AHVM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2Z2W7WLXFFPNTMLQZI2GK5AHVM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:2Z2W7WLXFFPNTMLQZI2GK5AHVM","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"3e8cef3ac6beceb35d3575d4bea652dfbf0d8cd5f6fb5dea34c912c6534e0f56","cross_cats_sorted":["math.IT","math.ST","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-02-12T07:34:33Z","title_canon_sha256":"9a0f523ad2b0b056bae42ccc85f38c9373551ed50a102a04fed092fc0df47f47"},"schema_version":"1.0","source":{"id":"1602.03969","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.03969","created_at":"2026-05-18T01:20:55Z"},{"alias_kind":"arxiv_version","alias_value":"1602.03969v1","created_at":"2026-05-18T01:20:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.03969","created_at":"2026-05-18T01:20:55Z"},{"alias_kind":"pith_short_12","alias_value":"2Z2W7WLXFFPN","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_16","alias_value":"2Z2W7WLXFFPNTMLQ","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_8","alias_value":"2Z2W7WLX","created_at":"2026-05-18T12:29:55Z"}],"graph_snapshots":[{"event_id":"sha256:b0cddfdbbcf942e1cd05fb048a94e00c72785c1c0faaf950d843d29a968c89ed","target":"graph","created_at":"2026-05-18T01:20:55Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Opportunistic detection rules (ODRs) are variants of fixed-sample-size detection rules in which the statistician is allowed to make an early decision on the alternative hypothesis opportunistically based on the sequentially observed samples. From a sequential decision perspective, ODRs are also mixtures of one-sided and truncated sequential detection rules. Several results regarding ODRs are established in this paper. In the finite regime, the maximum sample size is modeled either as a fixed finite number, or a geometric random variable with a fixed finite mean. For both cases, the correspondi","authors_text":"George V. Moustakides, H. Vincent Poor, Wenyi Zhang","cross_cats":["math.IT","math.ST","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-02-12T07:34:33Z","title":"Opportunistic Detection Rules: Finite and Asymptotic Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.03969","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:f300fb0e2ff466bb500e1693db7efed4ce8a0c795b3ff904fb8f408a1e07c93c","target":"record","created_at":"2026-05-18T01:20:55Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"3e8cef3ac6beceb35d3575d4bea652dfbf0d8cd5f6fb5dea34c912c6534e0f56","cross_cats_sorted":["math.IT","math.ST","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-02-12T07:34:33Z","title_canon_sha256":"9a0f523ad2b0b056bae42ccc85f38c9373551ed50a102a04fed092fc0df47f47"},"schema_version":"1.0","source":{"id":"1602.03969","kind":"arxiv","version":1}},"canonical_sha256":"d6756fd977295ed9b170ca34657407ab3961fbe3428ad7a6ac5f024bbd21b0ac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d6756fd977295ed9b170ca34657407ab3961fbe3428ad7a6ac5f024bbd21b0ac","first_computed_at":"2026-05-18T01:20:55.029809Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:20:55.029809Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZkDOLVD31ppZSny8nAsZ2o35qkWtbiMGU0WfFis+/y8eZz/5iBrXP3uo4MG8V34Xz4hrpz2D/TOjQM0DTgDECA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:20:55.030664Z","signed_message":"canonical_sha256_bytes"},"source_id":"1602.03969","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f300fb0e2ff466bb500e1693db7efed4ce8a0c795b3ff904fb8f408a1e07c93c","sha256:b0cddfdbbcf942e1cd05fb048a94e00c72785c1c0faaf950d843d29a968c89ed"],"state_sha256":"67f40be216fa17d18c81164a52e3511e7e2814f80261d63e537087687566e064"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ChNAS1tW9HCBp6SrDut+Kg56OeGXTxEelq2MhJ4/iMogvWR/ADCd9q4AH3v1egxH6jpWdxqY/UwFPQqrCLg9CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T05:02:55.373060Z","bundle_sha256":"fc7772d6b98679761306925f1568c1e99ac3692fb2b0e989062bfd33afb2c311"}}