{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2007:PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ","short_pith_number":"pith:PIZ3W5DL","schema_version":"1.0","canonical_sha256":"7a33bb746bb30d1414e5da6b9d421b1e7718a258550a11897f5c57fdf0230c10","source":{"kind":"arxiv","id":"physics/0702156","version":4},"attestation_state":"computed","paper":{"title":"Evaluation of three methods for calculating statistical significance when incorporating a systematic uncertainty into a test of the background-only hypothesis for a Poisson process","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.data-an","authors_text":"James T. Linnemann, Jordan Tucker, Robert D. Cousins","submitted_at":"2007-02-19T09:44:24Z","abstract_excerpt":"Hypothesis tests for the presence of new sources of Poisson counts amidst background processes are frequently performed in high energy physics (HEP), gamma ray astronomy (GRA), and other branches of science. While there are conceptual issues already when the mean rate of background is precisely known, the issues are even more difficult when the mean background rate has non-negligible uncertainty. After describing a variety of methods to be found in the HEP and GRA literature, we consider in detail three classes of algorithms and evaluate them over a wide range of parameter space, by the criter"},"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":"physics/0702156","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.data-an","submitted_at":"2007-02-19T09:44:24Z","cross_cats_sorted":[],"title_canon_sha256":"8c21548c8f4200441df5db63eaaf000663740ad0caa6ed01dcf348aa7dc9d2b1","abstract_canon_sha256":"bfe3ef693197b2647d78b2c983a9faeb072764ccfce9c09597d8a6ce83a6ae10"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T15:16:14.157150Z","signature_b64":"rchhveYBFr2g4zgBgeaCYxZVLUAhYdixfrdEbZlOY8G08u03/HJ+nyameJmskHRuZgVXYqN1nVm830gF4YthBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7a33bb746bb30d1414e5da6b9d421b1e7718a258550a11897f5c57fdf0230c10","last_reissued_at":"2026-07-04T15:16:14.156562Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T15:16:14.156562Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Evaluation of three methods for calculating statistical significance when incorporating a systematic uncertainty into a test of the background-only hypothesis for a Poisson process","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.data-an","authors_text":"James T. Linnemann, Jordan Tucker, Robert D. Cousins","submitted_at":"2007-02-19T09:44:24Z","abstract_excerpt":"Hypothesis tests for the presence of new sources of Poisson counts amidst background processes are frequently performed in high energy physics (HEP), gamma ray astronomy (GRA), and other branches of science. While there are conceptual issues already when the mean rate of background is precisely known, the issues are even more difficult when the mean background rate has non-negligible uncertainty. After describing a variety of methods to be found in the HEP and GRA literature, we consider in detail three classes of algorithms and evaluate them over a wide range of parameter space, by the criter"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"physics/0702156","kind":"arxiv","version":4},"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/physics/0702156/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":"physics/0702156","created_at":"2026-07-04T15:16:14.156636+00:00"},{"alias_kind":"arxiv_version","alias_value":"physics/0702156v4","created_at":"2026-07-04T15:16:14.156636+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.physics/0702156","created_at":"2026-07-04T15:16:14.156636+00:00"},{"alias_kind":"pith_short_12","alias_value":"PIZ3W5DLWMGR","created_at":"2026-07-04T15:16:14.156636+00:00"},{"alias_kind":"pith_short_16","alias_value":"PIZ3W5DLWMGRIFHF","created_at":"2026-07-04T15:16:14.156636+00:00"},{"alias_kind":"pith_short_8","alias_value":"PIZ3W5DL","created_at":"2026-07-04T15:16:14.156636+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2605.20048","citing_title":"Gaussian Process Eigenmodes for Statistical and Systematic Uncertainties in Template Fits","ref_index":31,"is_internal_anchor":true},{"citing_arxiv_id":"1007.1727","citing_title":"Asymptotic formulae for likelihood-based tests of new physics","ref_index":13,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ","json":"https://pith.science/pith/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ.json","graph_json":"https://pith.science/api/pith-number/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ/graph.json","events_json":"https://pith.science/api/pith-number/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ/events.json","paper":"https://pith.science/paper/PIZ3W5DL"},"agent_actions":{"view_html":"https://pith.science/pith/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ","download_json":"https://pith.science/pith/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ.json","view_paper":"https://pith.science/paper/PIZ3W5DL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=physics/0702156&json=true","fetch_graph":"https://pith.science/api/pith-number/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ/graph.json","fetch_events":"https://pith.science/api/pith-number/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ/action/storage_attestation","attest_author":"https://pith.science/pith/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ/action/author_attestation","sign_citation":"https://pith.science/pith/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ/action/citation_signature","submit_replication":"https://pith.science/pith/PIZ3W5DLWMGRIFHF3JVZ2QQ3DZ/action/replication_record"}},"created_at":"2026-07-04T15:16:14.156636+00:00","updated_at":"2026-07-04T15:16:14.156636+00:00"}