{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:UPXG3VZUJS3EQIKIIHSJCGC24G","short_pith_number":"pith:UPXG3VZU","canonical_record":{"source":{"id":"2205.05952","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2022-05-12T08:39:25Z","cross_cats_sorted":["astro-ph.IM","hep-ex","physics.data-an"],"title_canon_sha256":"c4bda512bfbbe1dbf223b2555454e93466b0a59e6368597eb8ba926d8e64609e","abstract_canon_sha256":"a80b8287d1eb57847fec715acbd002165e3c765aa16f82b20dcf050560f6331e"},"schema_version":"1.0"},"canonical_sha256":"a3ee6dd7344cb648214841e491185ae18a1729d4e9f6210c1eb69efafcdf60b4","source":{"kind":"arxiv","id":"2205.05952","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.05952","created_at":"2026-07-05T05:14:34Z"},{"alias_kind":"arxiv_version","alias_value":"2205.05952v2","created_at":"2026-07-05T05:14:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.05952","created_at":"2026-07-05T05:14:34Z"},{"alias_kind":"pith_short_12","alias_value":"UPXG3VZUJS3E","created_at":"2026-07-05T05:14:34Z"},{"alias_kind":"pith_short_16","alias_value":"UPXG3VZUJS3EQIKI","created_at":"2026-07-05T05:14:34Z"},{"alias_kind":"pith_short_8","alias_value":"UPXG3VZU","created_at":"2026-07-05T05:14:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:UPXG3VZUJS3EQIKIIHSJCGC24G","target":"record","payload":{"canonical_record":{"source":{"id":"2205.05952","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2022-05-12T08:39:25Z","cross_cats_sorted":["astro-ph.IM","hep-ex","physics.data-an"],"title_canon_sha256":"c4bda512bfbbe1dbf223b2555454e93466b0a59e6368597eb8ba926d8e64609e","abstract_canon_sha256":"a80b8287d1eb57847fec715acbd002165e3c765aa16f82b20dcf050560f6331e"},"schema_version":"1.0"},"canonical_sha256":"a3ee6dd7344cb648214841e491185ae18a1729d4e9f6210c1eb69efafcdf60b4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:14:34.634478Z","signature_b64":"I2M7QKXLU6VdMsXdmWT/NumErmBFfbP60vKIRpTcWiEtSUu1v724F5Ty4XfLkt1UnVgq58CWF/P0ubR62a7gAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a3ee6dd7344cb648214841e491185ae18a1729d4e9f6210c1eb69efafcdf60b4","last_reissued_at":"2026-07-05T05:14:34.634080Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:14:34.634080Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.05952","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":"2026-07-05T05:14:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L9/hui4nqukkxnKgO2xtamsLdIJMjGx2Jkt7UQqz9Z4083HNKEYk0jnoRj6v5FLg+al3ltKvuLaL221uD/ugBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:02:35.905648Z"},"content_sha256":"0debc59586fc04cae3829559bd28b2573bd122e6e93a4c78762c74e1dc158c8c","schema_version":"1.0","event_id":"sha256:0debc59586fc04cae3829559bd28b2573bd122e6e93a4c78762c74e1dc158c8c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:UPXG3VZUJS3EQIKIIHSJCGC24G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A method for approximating optimal statistical significances with machine-learned likelihoods","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.IM","hep-ex","physics.data-an"],"primary_cat":"hep-ph","authors_text":"Alejandro Szynkman, Andres D. Perez, Anibal D. Medina, Ernesto Arganda, Manuel Szewc, V\\'ictor Mart\\'in Lozano, Xabier Marcano","submitted_at":"2022-05-12T08:39:25Z","abstract_excerpt":"Machine-learning techniques have become fundamental in high-energy physics and, for new physics searches, it is crucial to know their performance in terms of experimental sensitivity, understood as the statistical significance of the signal-plus-background hypothesis over the background-only one. We present here a simple method that combines the power of current machine-learning techniques to face high-dimensional data with the likelihood-based inference tests used in traditional analyses, which allows us to estimate the sensitivity for both discovery and exclusion limits through a single para"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.05952","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2205.05952/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:14:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JZH9kVs3db+cPtZV+c6gsp1zhXlTulVnbKsbMgdETPP3R/qLf6Z5uO65jnm+brXCs3mR+JI6VYs0IR0xbGIoBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:02:35.906175Z"},"content_sha256":"a8b9dfd65ccf41b2289effbf906f69c9e3d1c1e6d1e0cc6de3e462db2b831e85","schema_version":"1.0","event_id":"sha256:a8b9dfd65ccf41b2289effbf906f69c9e3d1c1e6d1e0cc6de3e462db2b831e85"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UPXG3VZUJS3EQIKIIHSJCGC24G/bundle.json","state_url":"https://pith.science/pith/UPXG3VZUJS3EQIKIIHSJCGC24G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UPXG3VZUJS3EQIKIIHSJCGC24G/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":"2026-08-05T02:02:35Z","links":{"resolver":"https://pith.science/pith/UPXG3VZUJS3EQIKIIHSJCGC24G","bundle":"https://pith.science/pith/UPXG3VZUJS3EQIKIIHSJCGC24G/bundle.json","state":"https://pith.science/pith/UPXG3VZUJS3EQIKIIHSJCGC24G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UPXG3VZUJS3EQIKIIHSJCGC24G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:UPXG3VZUJS3EQIKIIHSJCGC24G","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":"a80b8287d1eb57847fec715acbd002165e3c765aa16f82b20dcf050560f6331e","cross_cats_sorted":["astro-ph.IM","hep-ex","physics.data-an"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2022-05-12T08:39:25Z","title_canon_sha256":"c4bda512bfbbe1dbf223b2555454e93466b0a59e6368597eb8ba926d8e64609e"},"schema_version":"1.0","source":{"id":"2205.05952","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.05952","created_at":"2026-07-05T05:14:34Z"},{"alias_kind":"arxiv_version","alias_value":"2205.05952v2","created_at":"2026-07-05T05:14:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.05952","created_at":"2026-07-05T05:14:34Z"},{"alias_kind":"pith_short_12","alias_value":"UPXG3VZUJS3E","created_at":"2026-07-05T05:14:34Z"},{"alias_kind":"pith_short_16","alias_value":"UPXG3VZUJS3EQIKI","created_at":"2026-07-05T05:14:34Z"},{"alias_kind":"pith_short_8","alias_value":"UPXG3VZU","created_at":"2026-07-05T05:14:34Z"}],"graph_snapshots":[{"event_id":"sha256:a8b9dfd65ccf41b2289effbf906f69c9e3d1c1e6d1e0cc6de3e462db2b831e85","target":"graph","created_at":"2026-07-05T05:14:34Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2205.05952/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine-learning techniques have become fundamental in high-energy physics and, for new physics searches, it is crucial to know their performance in terms of experimental sensitivity, understood as the statistical significance of the signal-plus-background hypothesis over the background-only one. We present here a simple method that combines the power of current machine-learning techniques to face high-dimensional data with the likelihood-based inference tests used in traditional analyses, which allows us to estimate the sensitivity for both discovery and exclusion limits through a single para","authors_text":"Alejandro Szynkman, Andres D. Perez, Anibal D. Medina, Ernesto Arganda, Manuel Szewc, V\\'ictor Mart\\'in Lozano, Xabier Marcano","cross_cats":["astro-ph.IM","hep-ex","physics.data-an"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2022-05-12T08:39:25Z","title":"A method for approximating optimal statistical significances with machine-learned likelihoods"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.05952","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":"sha256:0debc59586fc04cae3829559bd28b2573bd122e6e93a4c78762c74e1dc158c8c","target":"record","created_at":"2026-07-05T05:14:34Z","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":"a80b8287d1eb57847fec715acbd002165e3c765aa16f82b20dcf050560f6331e","cross_cats_sorted":["astro-ph.IM","hep-ex","physics.data-an"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"hep-ph","submitted_at":"2022-05-12T08:39:25Z","title_canon_sha256":"c4bda512bfbbe1dbf223b2555454e93466b0a59e6368597eb8ba926d8e64609e"},"schema_version":"1.0","source":{"id":"2205.05952","kind":"arxiv","version":2}},"canonical_sha256":"a3ee6dd7344cb648214841e491185ae18a1729d4e9f6210c1eb69efafcdf60b4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a3ee6dd7344cb648214841e491185ae18a1729d4e9f6210c1eb69efafcdf60b4","first_computed_at":"2026-07-05T05:14:34.634080Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:14:34.634080Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"I2M7QKXLU6VdMsXdmWT/NumErmBFfbP60vKIRpTcWiEtSUu1v724F5Ty4XfLkt1UnVgq58CWF/P0ubR62a7gAw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:14:34.634478Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.05952","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0debc59586fc04cae3829559bd28b2573bd122e6e93a4c78762c74e1dc158c8c","sha256:a8b9dfd65ccf41b2289effbf906f69c9e3d1c1e6d1e0cc6de3e462db2b831e85"],"state_sha256":"a06d3aff58418d42f447ffe3b56420ec0e2fb062e7dcebb5efe81f238c4ccd22"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CQG4Q7IzwdozGKep/a9PrG5LpymKmS8ZOqUbsQ2Vc1SbEtR3MlngBiSo/FujPpO51/tHYSKLWYNr1cUMVbEzCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T02:02:35.910823Z","bundle_sha256":"75717d4b89f366564833877ad2f2386488c6226bb919cf3c26570bfd1e007644"}}