{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:AIFCKOIFKDT7KOO6MAUWFT72LD","short_pith_number":"pith:AIFCKOIF","canonical_record":{"source":{"id":"2501.06964","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-12T22:49:32Z","cross_cats_sorted":["cs.HC"],"title_canon_sha256":"026e81879e13a756e6a7a755911785b1fb6af6b7a1013e2fd58aa083a55b71ee","abstract_canon_sha256":"440d6f702d2a7f2bc2378d9349c0407cf35e73526cc8f2ce54a2be354dd0271d"},"schema_version":"1.0"},"canonical_sha256":"020a25390550e7f539de602962cffa58f1edf1b81236a5710f9da4ec42cfca0d","source":{"kind":"arxiv","id":"2501.06964","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.06964","created_at":"2026-07-05T10:00:13Z"},{"alias_kind":"arxiv_version","alias_value":"2501.06964v1","created_at":"2026-07-05T10:00:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.06964","created_at":"2026-07-05T10:00:13Z"},{"alias_kind":"pith_short_12","alias_value":"AIFCKOIFKDT7","created_at":"2026-07-05T10:00:13Z"},{"alias_kind":"pith_short_16","alias_value":"AIFCKOIFKDT7KOO6","created_at":"2026-07-05T10:00:13Z"},{"alias_kind":"pith_short_8","alias_value":"AIFCKOIF","created_at":"2026-07-05T10:00:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:AIFCKOIFKDT7KOO6MAUWFT72LD","target":"record","payload":{"canonical_record":{"source":{"id":"2501.06964","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-12T22:49:32Z","cross_cats_sorted":["cs.HC"],"title_canon_sha256":"026e81879e13a756e6a7a755911785b1fb6af6b7a1013e2fd58aa083a55b71ee","abstract_canon_sha256":"440d6f702d2a7f2bc2378d9349c0407cf35e73526cc8f2ce54a2be354dd0271d"},"schema_version":"1.0"},"canonical_sha256":"020a25390550e7f539de602962cffa58f1edf1b81236a5710f9da4ec42cfca0d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:00:13.054623Z","signature_b64":"YXAlQonXj4Xr+zDb8XD1fOtughp1kGEHM3dPgTxCiMmeZufYbl9Ei85PBT0K5Yg0dRIRIT3FlElSgKC4Jd/8Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"020a25390550e7f539de602962cffa58f1edf1b81236a5710f9da4ec42cfca0d","last_reissued_at":"2026-07-05T10:00:13.054126Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:00:13.054126Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.06964","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":"2026-07-05T10:00:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nEGKJNgaIqKm1bt4Tnt2rSeIFgjZGcEOz8ELNe3+BuhOkfY9Ll/zQobnbb0eb6jVsfgX/UChN4XOk+QGaK1tAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T13:23:37.149842Z"},"content_sha256":"7b5eca1c0f9f9e38032238d74a7f9b88240185ec4bd36397c5387c2e357ed646","schema_version":"1.0","event_id":"sha256:7b5eca1c0f9f9e38032238d74a7f9b88240185ec4bd36397c5387c2e357ed646"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:AIFCKOIFKDT7KOO6MAUWFT72LD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Enhancing Patient-Centric Communication: Leveraging LLMs to Simulate Patient Perspectives","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.HC"],"primary_cat":"cs.AI","authors_text":"Haixu Tang, Jingwei Xiong, L. Jean Camp, Lucila Ohno-Machado, Qingyu Chen, Rui Zhu, Xinyao Ma, Zihao Wang","submitted_at":"2025-01-12T22:49:32Z","abstract_excerpt":"Large Language Models (LLMs) have demonstrated impressive capabilities in role-playing scenarios, particularly in simulating domain-specific experts using tailored prompts. This ability enables LLMs to adopt the persona of individuals with specific backgrounds, offering a cost-effective and efficient alternative to traditional, resource-intensive user studies. By mimicking human behavior, LLMs can anticipate responses based on concrete demographic or professional profiles. In this paper, we evaluate the effectiveness of LLMs in simulating individuals with diverse backgrounds and analyze the co"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.06964","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2501.06964/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":"2026-07-05T10:00:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uYvY67FSVA5loL0+LPDH4XhyV/SXAjeYnTuHI7Cv4PggJqC+etz+xU2sTS+DwmHcAtxXBWURPcFk2XT/vmUlBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T13:23:37.151181Z"},"content_sha256":"6c45982a7328d2c8fb6ca38dcf88f9efb1b8af1ecaa1e137f345c7e91f98083f","schema_version":"1.0","event_id":"sha256:6c45982a7328d2c8fb6ca38dcf88f9efb1b8af1ecaa1e137f345c7e91f98083f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AIFCKOIFKDT7KOO6MAUWFT72LD/bundle.json","state_url":"https://pith.science/pith/AIFCKOIFKDT7KOO6MAUWFT72LD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AIFCKOIFKDT7KOO6MAUWFT72LD/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":"2026-08-12T13:23:37Z","links":{"resolver":"https://pith.science/pith/AIFCKOIFKDT7KOO6MAUWFT72LD","bundle":"https://pith.science/pith/AIFCKOIFKDT7KOO6MAUWFT72LD/bundle.json","state":"https://pith.science/pith/AIFCKOIFKDT7KOO6MAUWFT72LD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AIFCKOIFKDT7KOO6MAUWFT72LD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:AIFCKOIFKDT7KOO6MAUWFT72LD","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":"440d6f702d2a7f2bc2378d9349c0407cf35e73526cc8f2ce54a2be354dd0271d","cross_cats_sorted":["cs.HC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-12T22:49:32Z","title_canon_sha256":"026e81879e13a756e6a7a755911785b1fb6af6b7a1013e2fd58aa083a55b71ee"},"schema_version":"1.0","source":{"id":"2501.06964","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.06964","created_at":"2026-07-05T10:00:13Z"},{"alias_kind":"arxiv_version","alias_value":"2501.06964v1","created_at":"2026-07-05T10:00:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.06964","created_at":"2026-07-05T10:00:13Z"},{"alias_kind":"pith_short_12","alias_value":"AIFCKOIFKDT7","created_at":"2026-07-05T10:00:13Z"},{"alias_kind":"pith_short_16","alias_value":"AIFCKOIFKDT7KOO6","created_at":"2026-07-05T10:00:13Z"},{"alias_kind":"pith_short_8","alias_value":"AIFCKOIF","created_at":"2026-07-05T10:00:13Z"}],"graph_snapshots":[{"event_id":"sha256:6c45982a7328d2c8fb6ca38dcf88f9efb1b8af1ecaa1e137f345c7e91f98083f","target":"graph","created_at":"2026-07-05T10:00:13Z","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/2501.06964/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have demonstrated impressive capabilities in role-playing scenarios, particularly in simulating domain-specific experts using tailored prompts. This ability enables LLMs to adopt the persona of individuals with specific backgrounds, offering a cost-effective and efficient alternative to traditional, resource-intensive user studies. By mimicking human behavior, LLMs can anticipate responses based on concrete demographic or professional profiles. In this paper, we evaluate the effectiveness of LLMs in simulating individuals with diverse backgrounds and analyze the co","authors_text":"Haixu Tang, Jingwei Xiong, L. Jean Camp, Lucila Ohno-Machado, Qingyu Chen, Rui Zhu, Xinyao Ma, Zihao Wang","cross_cats":["cs.HC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-12T22:49:32Z","title":"Enhancing Patient-Centric Communication: Leveraging LLMs to Simulate Patient Perspectives"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.06964","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":"sha256:7b5eca1c0f9f9e38032238d74a7f9b88240185ec4bd36397c5387c2e357ed646","target":"record","created_at":"2026-07-05T10:00:13Z","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":"440d6f702d2a7f2bc2378d9349c0407cf35e73526cc8f2ce54a2be354dd0271d","cross_cats_sorted":["cs.HC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-12T22:49:32Z","title_canon_sha256":"026e81879e13a756e6a7a755911785b1fb6af6b7a1013e2fd58aa083a55b71ee"},"schema_version":"1.0","source":{"id":"2501.06964","kind":"arxiv","version":1}},"canonical_sha256":"020a25390550e7f539de602962cffa58f1edf1b81236a5710f9da4ec42cfca0d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"020a25390550e7f539de602962cffa58f1edf1b81236a5710f9da4ec42cfca0d","first_computed_at":"2026-07-05T10:00:13.054126Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:00:13.054126Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YXAlQonXj4Xr+zDb8XD1fOtughp1kGEHM3dPgTxCiMmeZufYbl9Ei85PBT0K5Yg0dRIRIT3FlElSgKC4Jd/8Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:00:13.054623Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.06964","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7b5eca1c0f9f9e38032238d74a7f9b88240185ec4bd36397c5387c2e357ed646","sha256:6c45982a7328d2c8fb6ca38dcf88f9efb1b8af1ecaa1e137f345c7e91f98083f"],"state_sha256":"92fa8a241011f4abf7f79a872d6ddb216f90780982dccfdf9f1d56b040145996"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OUfQibmGK8pkLVLIsLMEUxpYzmDYO4keIwXCQdrjKd66i1vJKNvX4sqNcyQD6sBXmZe/abiMylPLE65hJ1PxAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T13:23:37.157976Z","bundle_sha256":"58a5a59c37c1aa6d964a6a6d31e1cd2876f7635a4e671018d0a418a47812182c"}}