{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:UHN6DEYVX55ZIKBBAGGHLCDUQB","short_pith_number":"pith:UHN6DEYV","canonical_record":{"source":{"id":"1406.2395","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2014-06-10T00:50:05Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"ad999fd89e7f2d93d1a03893852d29b90ca4d08b46675b3ef27aabcf7aa17a0d","abstract_canon_sha256":"88d6ee1a432249fa256c25ed0d337c61c0553705f57bff18bad39b9a615f5ae4"},"schema_version":"1.0"},"canonical_sha256":"a1dbe19315bf7b942821018c758874805a100018f059809626d44244c236bddd","source":{"kind":"arxiv","id":"1406.2395","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1406.2395","created_at":"2026-05-18T02:50:01Z"},{"alias_kind":"arxiv_version","alias_value":"1406.2395v1","created_at":"2026-05-18T02:50:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1406.2395","created_at":"2026-05-18T02:50:01Z"},{"alias_kind":"pith_short_12","alias_value":"UHN6DEYVX55Z","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_16","alias_value":"UHN6DEYVX55ZIKBB","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_8","alias_value":"UHN6DEYV","created_at":"2026-05-18T12:28:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:UHN6DEYVX55ZIKBBAGGHLCDUQB","target":"record","payload":{"canonical_record":{"source":{"id":"1406.2395","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2014-06-10T00:50:05Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"ad999fd89e7f2d93d1a03893852d29b90ca4d08b46675b3ef27aabcf7aa17a0d","abstract_canon_sha256":"88d6ee1a432249fa256c25ed0d337c61c0553705f57bff18bad39b9a615f5ae4"},"schema_version":"1.0"},"canonical_sha256":"a1dbe19315bf7b942821018c758874805a100018f059809626d44244c236bddd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:50:01.779175Z","signature_b64":"ZS6NxOr54Mye0MnSKVyNc7ppvGQ/wcyrLcM7BAOXOqX65xRehEfsxxj12AI0PcDGFoRt1EuEK7FsAzLzcatKDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a1dbe19315bf7b942821018c758874805a100018f059809626d44244c236bddd","last_reissued_at":"2026-05-18T02:50:01.778621Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:50:01.778621Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1406.2395","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":"2026-05-18T02:50:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4+CTCpnSI0CsD8eHUmJt9/OTau1Lsj634C8tLuuled8DhZFJKiF2HlBWNY6yzhPgsXfJXr5IBJirtNvpPtbGDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T19:25:46.566696Z"},"content_sha256":"6293f0ed666c26bf1315d2fe7f3bd6c145676c60f731bad792c1cd73ef352757","schema_version":"1.0","event_id":"sha256:6293f0ed666c26bf1315d2fe7f3bd6c145676c60f731bad792c1cd73ef352757"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:UHN6DEYVX55ZIKBBAGGHLCDUQB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ExpertBayes: Automatically refining manually built Bayesian networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.AI","authors_text":"Elizabeth Burnside, Ezilda Almeida, In\\^es Dutra, Jingwei Li, Pedro Ferreira, Tiago Vinhoza, Yirong Wu","submitted_at":"2014-06-10T00:50:05Z","abstract_excerpt":"Bayesian network structures are usually built using only the data and starting from an empty network or from a naive Bayes structure. Very often, in some domains, like medicine, a prior structure knowledge is already known. This structure can be automatically or manually refined in search for better performance models. In this work, we take Bayesian networks built by specialists and show that minor perturbations to this original network can yield better classifiers with a very small computational cost, while maintaining most of the intended meaning of the original model."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1406.2395","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":"2026-05-18T02:50:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+sH8r8c98XlVmByyeDXg6M3uVIt+012bv06PliCQxxZK7Jd3IGUG9Se48EUCwcMm7XGq2PzvAU4Wd6iwGe6ZCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T19:25:46.567476Z"},"content_sha256":"e4c589422043b5e051d07501f1b4eb3317b4f38477ec168ec8c4797586710cbd","schema_version":"1.0","event_id":"sha256:e4c589422043b5e051d07501f1b4eb3317b4f38477ec168ec8c4797586710cbd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UHN6DEYVX55ZIKBBAGGHLCDUQB/bundle.json","state_url":"https://pith.science/pith/UHN6DEYVX55ZIKBBAGGHLCDUQB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UHN6DEYVX55ZIKBBAGGHLCDUQB/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":"2026-05-31T19:25:46Z","links":{"resolver":"https://pith.science/pith/UHN6DEYVX55ZIKBBAGGHLCDUQB","bundle":"https://pith.science/pith/UHN6DEYVX55ZIKBBAGGHLCDUQB/bundle.json","state":"https://pith.science/pith/UHN6DEYVX55ZIKBBAGGHLCDUQB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UHN6DEYVX55ZIKBBAGGHLCDUQB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:UHN6DEYVX55ZIKBBAGGHLCDUQB","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":"88d6ee1a432249fa256c25ed0d337c61c0553705f57bff18bad39b9a615f5ae4","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2014-06-10T00:50:05Z","title_canon_sha256":"ad999fd89e7f2d93d1a03893852d29b90ca4d08b46675b3ef27aabcf7aa17a0d"},"schema_version":"1.0","source":{"id":"1406.2395","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1406.2395","created_at":"2026-05-18T02:50:01Z"},{"alias_kind":"arxiv_version","alias_value":"1406.2395v1","created_at":"2026-05-18T02:50:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1406.2395","created_at":"2026-05-18T02:50:01Z"},{"alias_kind":"pith_short_12","alias_value":"UHN6DEYVX55Z","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_16","alias_value":"UHN6DEYVX55ZIKBB","created_at":"2026-05-18T12:28:52Z"},{"alias_kind":"pith_short_8","alias_value":"UHN6DEYV","created_at":"2026-05-18T12:28:52Z"}],"graph_snapshots":[{"event_id":"sha256:e4c589422043b5e051d07501f1b4eb3317b4f38477ec168ec8c4797586710cbd","target":"graph","created_at":"2026-05-18T02:50:01Z","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":"Bayesian network structures are usually built using only the data and starting from an empty network or from a naive Bayes structure. Very often, in some domains, like medicine, a prior structure knowledge is already known. This structure can be automatically or manually refined in search for better performance models. In this work, we take Bayesian networks built by specialists and show that minor perturbations to this original network can yield better classifiers with a very small computational cost, while maintaining most of the intended meaning of the original model.","authors_text":"Elizabeth Burnside, Ezilda Almeida, In\\^es Dutra, Jingwei Li, Pedro Ferreira, Tiago Vinhoza, Yirong Wu","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2014-06-10T00:50:05Z","title":"ExpertBayes: Automatically refining manually built Bayesian networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1406.2395","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":"sha256:6293f0ed666c26bf1315d2fe7f3bd6c145676c60f731bad792c1cd73ef352757","target":"record","created_at":"2026-05-18T02:50:01Z","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":"88d6ee1a432249fa256c25ed0d337c61c0553705f57bff18bad39b9a615f5ae4","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2014-06-10T00:50:05Z","title_canon_sha256":"ad999fd89e7f2d93d1a03893852d29b90ca4d08b46675b3ef27aabcf7aa17a0d"},"schema_version":"1.0","source":{"id":"1406.2395","kind":"arxiv","version":1}},"canonical_sha256":"a1dbe19315bf7b942821018c758874805a100018f059809626d44244c236bddd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a1dbe19315bf7b942821018c758874805a100018f059809626d44244c236bddd","first_computed_at":"2026-05-18T02:50:01.778621Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:50:01.778621Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZS6NxOr54Mye0MnSKVyNc7ppvGQ/wcyrLcM7BAOXOqX65xRehEfsxxj12AI0PcDGFoRt1EuEK7FsAzLzcatKDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:50:01.779175Z","signed_message":"canonical_sha256_bytes"},"source_id":"1406.2395","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6293f0ed666c26bf1315d2fe7f3bd6c145676c60f731bad792c1cd73ef352757","sha256:e4c589422043b5e051d07501f1b4eb3317b4f38477ec168ec8c4797586710cbd"],"state_sha256":"f4a1320989ad7fb3d03ed05bd2c4031a6bdd40d229a3941f6ca9aaafca4b47f9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a0wvSLYkpTP4htMbnkcLteTjVv+HHy4kYzBf9zIAcFRiZLVR7nK48WCgsW4Mu9Qn5T7IHdqAAimCaZMgzjz5Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T19:25:46.571575Z","bundle_sha256":"8429be4bc8eeb0c17422d74f513ae8fa75be19f583d13f8a6958f5096e60e28e"}}