{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:BXHOMJEJIVTJEHY3QPQZ2CYKWA","short_pith_number":"pith:BXHOMJEJ","canonical_record":{"source":{"id":"1810.01570","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-03T02:53:04Z","cross_cats_sorted":[],"title_canon_sha256":"9a35761bfdc2224e4fd92fe6846989aa2f50ab95bc4d564d5aadc65557c4b87f","abstract_canon_sha256":"a5eb53603df60661fa109f9f469d25c633a264be7b907c8bc47f89b565573171"},"schema_version":"1.0"},"canonical_sha256":"0dcee624894566921f1b83e19d0b0ab035815c26da8f04727e12feaacd3f73e7","source":{"kind":"arxiv","id":"1810.01570","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.01570","created_at":"2026-05-18T00:04:11Z"},{"alias_kind":"arxiv_version","alias_value":"1810.01570v1","created_at":"2026-05-18T00:04:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.01570","created_at":"2026-05-18T00:04:11Z"},{"alias_kind":"pith_short_12","alias_value":"BXHOMJEJIVTJ","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"BXHOMJEJIVTJEHY3","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"BXHOMJEJ","created_at":"2026-05-18T12:32:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:BXHOMJEJIVTJEHY3QPQZ2CYKWA","target":"record","payload":{"canonical_record":{"source":{"id":"1810.01570","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-03T02:53:04Z","cross_cats_sorted":[],"title_canon_sha256":"9a35761bfdc2224e4fd92fe6846989aa2f50ab95bc4d564d5aadc65557c4b87f","abstract_canon_sha256":"a5eb53603df60661fa109f9f469d25c633a264be7b907c8bc47f89b565573171"},"schema_version":"1.0"},"canonical_sha256":"0dcee624894566921f1b83e19d0b0ab035815c26da8f04727e12feaacd3f73e7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:11.652748Z","signature_b64":"Wn9UK2cxD6Vv8U/HEBAvxB90PPTkkSTiZu9eJMBBbZu8Kq15hN3+UpKasZJny68smwghrLWFcsGO0EqrcaIMBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0dcee624894566921f1b83e19d0b0ab035815c26da8f04727e12feaacd3f73e7","last_reissued_at":"2026-05-18T00:04:11.652096Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:11.652096Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.01570","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":"2026-05-18T00:04:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eYsPR97TzatRq4U1CeOWUOvJSXed7YzFwbWinhzzMT8Jba3qB0F7X54bFryh+wjkdFykqrZEM+tVOblUYhwVBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T10:22:47.033796Z"},"content_sha256":"5294452fda98a49c69a82f878d19d3c026d1901f6628024e886eaa26effb9a42","schema_version":"1.0","event_id":"sha256:5294452fda98a49c69a82f878d19d3c026d1901f6628024e886eaa26effb9a42"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:BXHOMJEJIVTJEHY3QPQZ2CYKWA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Deep Learning Architecture for De-identification of Patient Notes: Implementation and Evaluation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Kaung Khin, Philipp Burckhardt, Rema Padman","submitted_at":"2018-10-03T02:53:04Z","abstract_excerpt":"De-identification is the process of removing 18 protected health information (PHI) from clinical notes in order for the text to be considered not individually identifiable. Recent advances in natural language processing (NLP) has allowed for the use of deep learning techniques for the task of de-identification. In this paper, we present a deep learning architecture that builds on the latest NLP advances by incorporating deep contextualized word embeddings and variational drop out Bi-LSTMs. We test this architecture on two gold standard datasets and show that the architecture achieves state-of-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.01570","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":"2026-05-18T00:04:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YvxDvY7MdthWmIn6U1Z271fmkLfgp64cGejPSwDK2MzDWLtlErzudEjkwkF3GIy06QAQAaA6RJcKmuObr/okBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T10:22:47.034188Z"},"content_sha256":"27561aa3b14ffd0d04d3e42b5f2e29b3e359b622a1b2f014c43b9ec504a0090a","schema_version":"1.0","event_id":"sha256:27561aa3b14ffd0d04d3e42b5f2e29b3e359b622a1b2f014c43b9ec504a0090a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BXHOMJEJIVTJEHY3QPQZ2CYKWA/bundle.json","state_url":"https://pith.science/pith/BXHOMJEJIVTJEHY3QPQZ2CYKWA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BXHOMJEJIVTJEHY3QPQZ2CYKWA/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":"2026-06-03T10:22:47Z","links":{"resolver":"https://pith.science/pith/BXHOMJEJIVTJEHY3QPQZ2CYKWA","bundle":"https://pith.science/pith/BXHOMJEJIVTJEHY3QPQZ2CYKWA/bundle.json","state":"https://pith.science/pith/BXHOMJEJIVTJEHY3QPQZ2CYKWA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BXHOMJEJIVTJEHY3QPQZ2CYKWA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:BXHOMJEJIVTJEHY3QPQZ2CYKWA","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":"a5eb53603df60661fa109f9f469d25c633a264be7b907c8bc47f89b565573171","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-03T02:53:04Z","title_canon_sha256":"9a35761bfdc2224e4fd92fe6846989aa2f50ab95bc4d564d5aadc65557c4b87f"},"schema_version":"1.0","source":{"id":"1810.01570","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.01570","created_at":"2026-05-18T00:04:11Z"},{"alias_kind":"arxiv_version","alias_value":"1810.01570v1","created_at":"2026-05-18T00:04:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.01570","created_at":"2026-05-18T00:04:11Z"},{"alias_kind":"pith_short_12","alias_value":"BXHOMJEJIVTJ","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"BXHOMJEJIVTJEHY3","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"BXHOMJEJ","created_at":"2026-05-18T12:32:16Z"}],"graph_snapshots":[{"event_id":"sha256:27561aa3b14ffd0d04d3e42b5f2e29b3e359b622a1b2f014c43b9ec504a0090a","target":"graph","created_at":"2026-05-18T00:04:11Z","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":"De-identification is the process of removing 18 protected health information (PHI) from clinical notes in order for the text to be considered not individually identifiable. Recent advances in natural language processing (NLP) has allowed for the use of deep learning techniques for the task of de-identification. In this paper, we present a deep learning architecture that builds on the latest NLP advances by incorporating deep contextualized word embeddings and variational drop out Bi-LSTMs. We test this architecture on two gold standard datasets and show that the architecture achieves state-of-","authors_text":"Kaung Khin, Philipp Burckhardt, Rema Padman","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-03T02:53:04Z","title":"A Deep Learning Architecture for De-identification of Patient Notes: Implementation and Evaluation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.01570","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":"sha256:5294452fda98a49c69a82f878d19d3c026d1901f6628024e886eaa26effb9a42","target":"record","created_at":"2026-05-18T00:04:11Z","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":"a5eb53603df60661fa109f9f469d25c633a264be7b907c8bc47f89b565573171","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-03T02:53:04Z","title_canon_sha256":"9a35761bfdc2224e4fd92fe6846989aa2f50ab95bc4d564d5aadc65557c4b87f"},"schema_version":"1.0","source":{"id":"1810.01570","kind":"arxiv","version":1}},"canonical_sha256":"0dcee624894566921f1b83e19d0b0ab035815c26da8f04727e12feaacd3f73e7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0dcee624894566921f1b83e19d0b0ab035815c26da8f04727e12feaacd3f73e7","first_computed_at":"2026-05-18T00:04:11.652096Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:04:11.652096Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Wn9UK2cxD6Vv8U/HEBAvxB90PPTkkSTiZu9eJMBBbZu8Kq15hN3+UpKasZJny68smwghrLWFcsGO0EqrcaIMBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:04:11.652748Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.01570","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5294452fda98a49c69a82f878d19d3c026d1901f6628024e886eaa26effb9a42","sha256:27561aa3b14ffd0d04d3e42b5f2e29b3e359b622a1b2f014c43b9ec504a0090a"],"state_sha256":"cc265af78e4019513f1244955787d26a9541bf4822ee739ad5aa43fe09ab4fd6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"daHUCmOPojabH8/DkxKZNN6ivuqCRPcW+/verVxImYl6SS6yyxCOeRNWdQI2s4Lth4tRyHji873YJkki/y15BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T10:22:47.036271Z","bundle_sha256":"b95021a2a35caabd34bbcef11bbba273f9485d992d626f2b7348317a2961cc08"}}