{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:P3SOUM2VZLAOBBAQ7WMFOHYEXO","short_pith_number":"pith:P3SOUM2V","canonical_record":{"source":{"id":"1410.0950","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-10-03T19:40:53Z","cross_cats_sorted":[],"title_canon_sha256":"8e93d4ba19a3c0fee25ea29ce13acd6ccc41fde02c2c0f278768a1abd119ae12","abstract_canon_sha256":"490bbd684234569d2279387d27ffab20da94bb6f6e76876fb1daa25fb9a47355"},"schema_version":"1.0"},"canonical_sha256":"7ee4ea3355cac0e08410fd98571f04bba71091ba3c720c4c44c66d6cac176bd8","source":{"kind":"arxiv","id":"1410.0950","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1410.0950","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"arxiv_version","alias_value":"1410.0950v2","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1410.0950","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"pith_short_12","alias_value":"P3SOUM2VZLAO","created_at":"2026-05-18T12:28:43Z"},{"alias_kind":"pith_short_16","alias_value":"P3SOUM2VZLAOBBAQ","created_at":"2026-05-18T12:28:43Z"},{"alias_kind":"pith_short_8","alias_value":"P3SOUM2V","created_at":"2026-05-18T12:28:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:P3SOUM2VZLAOBBAQ7WMFOHYEXO","target":"record","payload":{"canonical_record":{"source":{"id":"1410.0950","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-10-03T19:40:53Z","cross_cats_sorted":[],"title_canon_sha256":"8e93d4ba19a3c0fee25ea29ce13acd6ccc41fde02c2c0f278768a1abd119ae12","abstract_canon_sha256":"490bbd684234569d2279387d27ffab20da94bb6f6e76876fb1daa25fb9a47355"},"schema_version":"1.0"},"canonical_sha256":"7ee4ea3355cac0e08410fd98571f04bba71091ba3c720c4c44c66d6cac176bd8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:38:38.570676Z","signature_b64":"hAbcu09HiGSJgJojlTYm5I1ibn5gGLfvc6es1ckc/q9odaizM9TP8qFGVVL0ithH154esx/fZIMDXp7NFPT6Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7ee4ea3355cac0e08410fd98571f04bba71091ba3c720c4c44c66d6cac176bd8","last_reissued_at":"2026-05-18T02:38:38.570261Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:38:38.570261Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1410.0950","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:38:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1k7PxGhbb5ijC5JfZD6s8rF+fwJzbsHR5gd8nxRuffk5Q3YA93IR5ftWCzZU3I43iUUcHpQ3mreH8b8NCMhJAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T03:07:58.250144Z"},"content_sha256":"32cbeec85582d38057816ec6d7d26087da3da829ccd28117c31b2ae72ddd6459","schema_version":"1.0","event_id":"sha256:32cbeec85582d38057816ec6d7d26087da3da829ccd28117c31b2ae72ddd6459"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:P3SOUM2VZLAOBBAQ7WMFOHYEXO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adaptive Sensing Resource Allocation Over Multiple Hypothesis Tests","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Dennis Wei","submitted_at":"2014-10-03T19:40:53Z","abstract_excerpt":"This paper considers multiple binary hypothesis tests with adaptive allocation of sensing resources from a shared budget over a small number of stages. A Bayesian formulation is provided for the multistage allocation problem of minimizing the sum of Bayes risks, which is then recast as a dynamic program. In the single-stage case, the problem is a non-convex optimization, for which an algorithm composed of a series of parallel one-dimensional minimizations is presented. This algorithm ensures a global minimum under a sufficient condition. In the multistage case, the approximate dynamic programm"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1410.0950","kind":"arxiv","version":2},"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":"2026-05-18T02:38:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZoUeAIE+gGbDyjejdXSQzOemR8BmDd8VqQiX6Joe4/5/2jteVVe/BniU6lL7xA+QbG81UhX/1/t7goDeJz5HCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T03:07:58.251187Z"},"content_sha256":"776961dd6e4f819dd577aaa22f259445b91950851daa65d7b880797a10cc8df1","schema_version":"1.0","event_id":"sha256:776961dd6e4f819dd577aaa22f259445b91950851daa65d7b880797a10cc8df1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P3SOUM2VZLAOBBAQ7WMFOHYEXO/bundle.json","state_url":"https://pith.science/pith/P3SOUM2VZLAOBBAQ7WMFOHYEXO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P3SOUM2VZLAOBBAQ7WMFOHYEXO/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":"2026-05-20T03:07:58Z","links":{"resolver":"https://pith.science/pith/P3SOUM2VZLAOBBAQ7WMFOHYEXO","bundle":"https://pith.science/pith/P3SOUM2VZLAOBBAQ7WMFOHYEXO/bundle.json","state":"https://pith.science/pith/P3SOUM2VZLAOBBAQ7WMFOHYEXO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P3SOUM2VZLAOBBAQ7WMFOHYEXO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:P3SOUM2VZLAOBBAQ7WMFOHYEXO","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":"490bbd684234569d2279387d27ffab20da94bb6f6e76876fb1daa25fb9a47355","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-10-03T19:40:53Z","title_canon_sha256":"8e93d4ba19a3c0fee25ea29ce13acd6ccc41fde02c2c0f278768a1abd119ae12"},"schema_version":"1.0","source":{"id":"1410.0950","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1410.0950","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"arxiv_version","alias_value":"1410.0950v2","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1410.0950","created_at":"2026-05-18T02:38:38Z"},{"alias_kind":"pith_short_12","alias_value":"P3SOUM2VZLAO","created_at":"2026-05-18T12:28:43Z"},{"alias_kind":"pith_short_16","alias_value":"P3SOUM2VZLAOBBAQ","created_at":"2026-05-18T12:28:43Z"},{"alias_kind":"pith_short_8","alias_value":"P3SOUM2V","created_at":"2026-05-18T12:28:43Z"}],"graph_snapshots":[{"event_id":"sha256:776961dd6e4f819dd577aaa22f259445b91950851daa65d7b880797a10cc8df1","target":"graph","created_at":"2026-05-18T02:38:38Z","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":"This paper considers multiple binary hypothesis tests with adaptive allocation of sensing resources from a shared budget over a small number of stages. A Bayesian formulation is provided for the multistage allocation problem of minimizing the sum of Bayes risks, which is then recast as a dynamic program. In the single-stage case, the problem is a non-convex optimization, for which an algorithm composed of a series of parallel one-dimensional minimizations is presented. This algorithm ensures a global minimum under a sufficient condition. In the multistage case, the approximate dynamic programm","authors_text":"Dennis Wei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-10-03T19:40:53Z","title":"Adaptive Sensing Resource Allocation Over Multiple Hypothesis Tests"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1410.0950","kind":"arxiv","version":2},"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":"sha256:32cbeec85582d38057816ec6d7d26087da3da829ccd28117c31b2ae72ddd6459","target":"record","created_at":"2026-05-18T02:38:38Z","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":"490bbd684234569d2279387d27ffab20da94bb6f6e76876fb1daa25fb9a47355","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-10-03T19:40:53Z","title_canon_sha256":"8e93d4ba19a3c0fee25ea29ce13acd6ccc41fde02c2c0f278768a1abd119ae12"},"schema_version":"1.0","source":{"id":"1410.0950","kind":"arxiv","version":2}},"canonical_sha256":"7ee4ea3355cac0e08410fd98571f04bba71091ba3c720c4c44c66d6cac176bd8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7ee4ea3355cac0e08410fd98571f04bba71091ba3c720c4c44c66d6cac176bd8","first_computed_at":"2026-05-18T02:38:38.570261Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:38:38.570261Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hAbcu09HiGSJgJojlTYm5I1ibn5gGLfvc6es1ckc/q9odaizM9TP8qFGVVL0ithH154esx/fZIMDXp7NFPT6Dw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:38:38.570676Z","signed_message":"canonical_sha256_bytes"},"source_id":"1410.0950","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:32cbeec85582d38057816ec6d7d26087da3da829ccd28117c31b2ae72ddd6459","sha256:776961dd6e4f819dd577aaa22f259445b91950851daa65d7b880797a10cc8df1"],"state_sha256":"93bc8203a084e2ab72c14694a07002fdb3bf84da09c888cb32a89d345d06fdba"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p7nvl74d8YDaUOQZSSTaZ8OcKki7KWA0BIDsnUdz+xBxDNXAKNTOjvJ218rvfR6tI3BEiVtbe730CdqULLYqCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-20T03:07:58.256555Z","bundle_sha256":"612ca790403247e1001bae896b5b6cc4224e456362165351ffa60518a8165416"}}