{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:3MAQYH4BSF7LSAY2UHO7M6ZERK","short_pith_number":"pith:3MAQYH4B","canonical_record":{"source":{"id":"2402.00160","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-31T20:31:56Z","cross_cats_sorted":[],"title_canon_sha256":"7579cf8aa56fcbacff1de63364dfe2e1907f599dcc72e16b7342500fdc756d91","abstract_canon_sha256":"df13f21c80147aa6ab8eadea6daae7bee345c547769cf2cc65e94d455095e324"},"schema_version":"1.0"},"canonical_sha256":"db010c1f81917eb9031aa1ddf67b248aba72dac08af1566f4a47ae3137d617c7","source":{"kind":"arxiv","id":"2402.00160","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.00160","created_at":"2026-07-05T11:32:14Z"},{"alias_kind":"arxiv_version","alias_value":"2402.00160v2","created_at":"2026-07-05T11:32:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00160","created_at":"2026-07-05T11:32:14Z"},{"alias_kind":"pith_short_12","alias_value":"3MAQYH4BSF7L","created_at":"2026-07-05T11:32:14Z"},{"alias_kind":"pith_short_16","alias_value":"3MAQYH4BSF7LSAY2","created_at":"2026-07-05T11:32:14Z"},{"alias_kind":"pith_short_8","alias_value":"3MAQYH4B","created_at":"2026-07-05T11:32:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:3MAQYH4BSF7LSAY2UHO7M6ZERK","target":"record","payload":{"canonical_record":{"source":{"id":"2402.00160","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-31T20:31:56Z","cross_cats_sorted":[],"title_canon_sha256":"7579cf8aa56fcbacff1de63364dfe2e1907f599dcc72e16b7342500fdc756d91","abstract_canon_sha256":"df13f21c80147aa6ab8eadea6daae7bee345c547769cf2cc65e94d455095e324"},"schema_version":"1.0"},"canonical_sha256":"db010c1f81917eb9031aa1ddf67b248aba72dac08af1566f4a47ae3137d617c7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:32:14.378447Z","signature_b64":"lT1BmaWOCbKF6za59HP0IVzEVSlFF62vLy9FXA8wj1r8yf9mnH6gHyUxOPBqlnuj2Fuk/Ojfa+EKvhET5HQHAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"db010c1f81917eb9031aa1ddf67b248aba72dac08af1566f4a47ae3137d617c7","last_reissued_at":"2026-07-05T11:32:14.377922Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:32:14.377922Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.00160","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":"2026-07-05T11:32:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fABtAjb+Wyfm3jQNBnLkQKwOVkk+CNYPuMm/AeqvwbG8F+U7hvXY1dX3p2w4AX7/XmHX1dchECpXcaCrmLu5Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T00:14:15.790068Z"},"content_sha256":"4b34a8508673e9ce5f08761d2883da29b495255f5aa45a66605bc296d22b3fd1","schema_version":"1.0","event_id":"sha256:4b34a8508673e9ce5f08761d2883da29b495255f5aa45a66605bc296d22b3fd1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:3MAQYH4BSF7LSAY2UHO7M6ZERK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Emergency Department Decision Support using Clinical Pseudo-notes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Akos Rudas, Alex Chen, Jeffrey N. Chiang, Jennifer Fang, Kyoka Ono, Simon A. Lee, Sujay Jain","submitted_at":"2024-01-31T20:31:56Z","abstract_excerpt":"In this work, we introduce the Multiple Embedding Model for EHR (MEME), an approach that serializes multimodal EHR tabular data into text using pseudo-notes, mimicking clinical text generation. This conversion not only preserves better representations of categorical data and learns contexts but also enables the effective employment of pretrained foundation models for rich feature representation. To address potential issues with context length, our framework encodes embeddings for each EHR modality separately. We demonstrate the effectiveness of MEME by applying it to several decision support t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00160","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/2402.00160/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":"2026-07-05T11:32:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fn2Qq0MDf0K47e3mgfyJGbuYq0mWCPNZCbiVvFaS73laWFgdyBkxj7DiBdjpellCkRNEiU+VPiOdjnM8iCjGAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T00:14:15.790552Z"},"content_sha256":"290126cb625870c0f79c7080b07a1def335e997291888375acc70a020dd3c915","schema_version":"1.0","event_id":"sha256:290126cb625870c0f79c7080b07a1def335e997291888375acc70a020dd3c915"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3MAQYH4BSF7LSAY2UHO7M6ZERK/bundle.json","state_url":"https://pith.science/pith/3MAQYH4BSF7LSAY2UHO7M6ZERK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3MAQYH4BSF7LSAY2UHO7M6ZERK/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":"2026-08-05T00:14:15Z","links":{"resolver":"https://pith.science/pith/3MAQYH4BSF7LSAY2UHO7M6ZERK","bundle":"https://pith.science/pith/3MAQYH4BSF7LSAY2UHO7M6ZERK/bundle.json","state":"https://pith.science/pith/3MAQYH4BSF7LSAY2UHO7M6ZERK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3MAQYH4BSF7LSAY2UHO7M6ZERK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:3MAQYH4BSF7LSAY2UHO7M6ZERK","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":"df13f21c80147aa6ab8eadea6daae7bee345c547769cf2cc65e94d455095e324","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-31T20:31:56Z","title_canon_sha256":"7579cf8aa56fcbacff1de63364dfe2e1907f599dcc72e16b7342500fdc756d91"},"schema_version":"1.0","source":{"id":"2402.00160","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.00160","created_at":"2026-07-05T11:32:14Z"},{"alias_kind":"arxiv_version","alias_value":"2402.00160v2","created_at":"2026-07-05T11:32:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00160","created_at":"2026-07-05T11:32:14Z"},{"alias_kind":"pith_short_12","alias_value":"3MAQYH4BSF7L","created_at":"2026-07-05T11:32:14Z"},{"alias_kind":"pith_short_16","alias_value":"3MAQYH4BSF7LSAY2","created_at":"2026-07-05T11:32:14Z"},{"alias_kind":"pith_short_8","alias_value":"3MAQYH4B","created_at":"2026-07-05T11:32:14Z"}],"graph_snapshots":[{"event_id":"sha256:290126cb625870c0f79c7080b07a1def335e997291888375acc70a020dd3c915","target":"graph","created_at":"2026-07-05T11:32:14Z","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/2402.00160/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work, we introduce the Multiple Embedding Model for EHR (MEME), an approach that serializes multimodal EHR tabular data into text using pseudo-notes, mimicking clinical text generation. This conversion not only preserves better representations of categorical data and learns contexts but also enables the effective employment of pretrained foundation models for rich feature representation. To address potential issues with context length, our framework encodes embeddings for each EHR modality separately. We demonstrate the effectiveness of MEME by applying it to several decision support t","authors_text":"Akos Rudas, Alex Chen, Jeffrey N. Chiang, Jennifer Fang, Kyoka Ono, Simon A. Lee, Sujay Jain","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-31T20:31:56Z","title":"Emergency Department Decision Support using Clinical Pseudo-notes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00160","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":"sha256:4b34a8508673e9ce5f08761d2883da29b495255f5aa45a66605bc296d22b3fd1","target":"record","created_at":"2026-07-05T11:32:14Z","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":"df13f21c80147aa6ab8eadea6daae7bee345c547769cf2cc65e94d455095e324","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-31T20:31:56Z","title_canon_sha256":"7579cf8aa56fcbacff1de63364dfe2e1907f599dcc72e16b7342500fdc756d91"},"schema_version":"1.0","source":{"id":"2402.00160","kind":"arxiv","version":2}},"canonical_sha256":"db010c1f81917eb9031aa1ddf67b248aba72dac08af1566f4a47ae3137d617c7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"db010c1f81917eb9031aa1ddf67b248aba72dac08af1566f4a47ae3137d617c7","first_computed_at":"2026-07-05T11:32:14.377922Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:32:14.377922Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lT1BmaWOCbKF6za59HP0IVzEVSlFF62vLy9FXA8wj1r8yf9mnH6gHyUxOPBqlnuj2Fuk/Ojfa+EKvhET5HQHAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:32:14.378447Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.00160","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4b34a8508673e9ce5f08761d2883da29b495255f5aa45a66605bc296d22b3fd1","sha256:290126cb625870c0f79c7080b07a1def335e997291888375acc70a020dd3c915"],"state_sha256":"7827670f2f71179d963d9f9895ac3df512dd33474fde38553319f1de7f04b624"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dhXnGvspqqSjgXKq6zBwqmnJTCfLDlz3N7ntsDXBS80Kd7RqIscC9YmvGoZZ7G4fQnCyd7qfP/UjekNiLTB9BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T00:14:15.793884Z","bundle_sha256":"8d0591d82785572921f422a264cd4d15e1c778363dd957040d07ef8d5a78ac21"}}