{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:F36N47THHWUBLWIPESJD63UCA2","short_pith_number":"pith:F36N47TH","schema_version":"1.0","canonical_sha256":"2efcde7e673da815d90f24923f6e820685f42cadb322fe94ecd60f8f6205d8e8","source":{"kind":"arxiv","id":"1207.4170","version":1},"attestation_state":"computed","paper":{"title":"Evidence-invariant Sensitivity Bounds","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Linda C. van der Gaag, Silja Renooij","submitted_at":"2012-07-11T15:06:14Z","abstract_excerpt":"The sensitivities revealed by a sensitivity analysis of a probabilistic network typically depend on the entered evidence. For a real-life network therefore, the analysis is performed a number of times, with different evidence. Although efficient algorithms for sensitivity analysis exist, a complete analysis is often infeasible because of the large range of possible combinations of observations. In this paper we present a method for studying sensitivities that are invariant to the evidence entered. Our method builds upon the idea of establishing bounds between which a parameter can be varied wi"},"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":"1207.4170","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2012-07-11T15:06:14Z","cross_cats_sorted":[],"title_canon_sha256":"c01f62170ed5cc09ca28c30f177d98c23657aaf6a3afdf2bec752d9e1a437457","abstract_canon_sha256":"f261df1a16ae297d822a8f0afd31a4334d33f3f05430f8f26b8cd274682e49fe"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:50:47.463435Z","signature_b64":"MX9bU80HXCQiCj7ZZdqPxOIlGqeoaAZcfddsDp61AbYuZHIwRryRjCIZsWRWiCgwwBOB/2d0EYwNsxCjVAQdCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2efcde7e673da815d90f24923f6e820685f42cadb322fe94ecd60f8f6205d8e8","last_reissued_at":"2026-05-18T03:50:47.462745Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:50:47.462745Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Evidence-invariant Sensitivity Bounds","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Linda C. van der Gaag, Silja Renooij","submitted_at":"2012-07-11T15:06:14Z","abstract_excerpt":"The sensitivities revealed by a sensitivity analysis of a probabilistic network typically depend on the entered evidence. For a real-life network therefore, the analysis is performed a number of times, with different evidence. Although efficient algorithms for sensitivity analysis exist, a complete analysis is often infeasible because of the large range of possible combinations of observations. In this paper we present a method for studying sensitivities that are invariant to the evidence entered. Our method builds upon the idea of establishing bounds between which a parameter can be varied wi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1207.4170","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":"1207.4170","created_at":"2026-05-18T03:50:47.462834+00:00"},{"alias_kind":"arxiv_version","alias_value":"1207.4170v1","created_at":"2026-05-18T03:50:47.462834+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1207.4170","created_at":"2026-05-18T03:50:47.462834+00:00"},{"alias_kind":"pith_short_12","alias_value":"F36N47THHWUB","created_at":"2026-05-18T12:27:04.183437+00:00"},{"alias_kind":"pith_short_16","alias_value":"F36N47THHWUBLWIP","created_at":"2026-05-18T12:27:04.183437+00:00"},{"alias_kind":"pith_short_8","alias_value":"F36N47TH","created_at":"2026-05-18T12:27:04.183437+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/F36N47THHWUBLWIPESJD63UCA2","json":"https://pith.science/pith/F36N47THHWUBLWIPESJD63UCA2.json","graph_json":"https://pith.science/api/pith-number/F36N47THHWUBLWIPESJD63UCA2/graph.json","events_json":"https://pith.science/api/pith-number/F36N47THHWUBLWIPESJD63UCA2/events.json","paper":"https://pith.science/paper/F36N47TH"},"agent_actions":{"view_html":"https://pith.science/pith/F36N47THHWUBLWIPESJD63UCA2","download_json":"https://pith.science/pith/F36N47THHWUBLWIPESJD63UCA2.json","view_paper":"https://pith.science/paper/F36N47TH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1207.4170&json=true","fetch_graph":"https://pith.science/api/pith-number/F36N47THHWUBLWIPESJD63UCA2/graph.json","fetch_events":"https://pith.science/api/pith-number/F36N47THHWUBLWIPESJD63UCA2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/F36N47THHWUBLWIPESJD63UCA2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/F36N47THHWUBLWIPESJD63UCA2/action/storage_attestation","attest_author":"https://pith.science/pith/F36N47THHWUBLWIPESJD63UCA2/action/author_attestation","sign_citation":"https://pith.science/pith/F36N47THHWUBLWIPESJD63UCA2/action/citation_signature","submit_replication":"https://pith.science/pith/F36N47THHWUBLWIPESJD63UCA2/action/replication_record"}},"created_at":"2026-05-18T03:50:47.462834+00:00","updated_at":"2026-05-18T03:50:47.462834+00:00"}