{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:B3ABAYYP3EEX65MXJ2KZXMHEEZ","short_pith_number":"pith:B3ABAYYP","canonical_record":{"source":{"id":"2306.10070","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2023-06-15T20:19:08Z","cross_cats_sorted":["cs.AI","cs.CL","q-bio.QM"],"title_canon_sha256":"8ab94364e726da0df209185e1e40e0f03c3c4aad6ec382013c16e19ab4a3ad6b","abstract_canon_sha256":"244922b237d53c8f4514113bc4fe03c8e6748d0168ef306aa775f38283054d6e"},"schema_version":"1.0"},"canonical_sha256":"0ec010630fd9097f75974e959bb0e4267ac2597ccbeba787d768346a87aa04d2","source":{"kind":"arxiv","id":"2306.10070","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.10070","created_at":"2026-07-05T07:33:17Z"},{"alias_kind":"arxiv_version","alias_value":"2306.10070v2","created_at":"2026-07-05T07:33:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.10070","created_at":"2026-07-05T07:33:17Z"},{"alias_kind":"pith_short_12","alias_value":"B3ABAYYP3EEX","created_at":"2026-07-05T07:33:17Z"},{"alias_kind":"pith_short_16","alias_value":"B3ABAYYP3EEX65MX","created_at":"2026-07-05T07:33:17Z"},{"alias_kind":"pith_short_8","alias_value":"B3ABAYYP","created_at":"2026-07-05T07:33:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:B3ABAYYP3EEX65MXJ2KZXMHEEZ","target":"record","payload":{"canonical_record":{"source":{"id":"2306.10070","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2023-06-15T20:19:08Z","cross_cats_sorted":["cs.AI","cs.CL","q-bio.QM"],"title_canon_sha256":"8ab94364e726da0df209185e1e40e0f03c3c4aad6ec382013c16e19ab4a3ad6b","abstract_canon_sha256":"244922b237d53c8f4514113bc4fe03c8e6748d0168ef306aa775f38283054d6e"},"schema_version":"1.0"},"canonical_sha256":"0ec010630fd9097f75974e959bb0e4267ac2597ccbeba787d768346a87aa04d2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:33:17.143694Z","signature_b64":"1Y0Lozg1qoKjZIzCcqoDQDcCRBnUJB1qVSgBFDHT2AGq+Qa9oOkoY0BTKIN4CaE2RXMFzcWZQP0LzitdIW/0Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0ec010630fd9097f75974e959bb0e4267ac2597ccbeba787d768346a87aa04d2","last_reissued_at":"2026-07-05T07:33:17.143045Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:33:17.143045Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.10070","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":"2026-07-05T07:33:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uq6acQXTnKxK4mpPbFEWWIS6nYCF74TFTAlIx7DDx4yVilryLPEMFvKAkj2xzZnF4bvojulSsRFOBRo3HllCCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T15:43:18.849284Z"},"content_sha256":"8884e6e5f822323dc54eddd0dee2c096a4f6d9e8db0ec80a06fd7d31a25c48a3","schema_version":"1.0","event_id":"sha256:8884e6e5f822323dc54eddd0dee2c096a4f6d9e8db0ec80a06fd7d31a25c48a3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:B3ABAYYP3EEX65MXJ2KZXMHEEZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","q-bio.QM"],"primary_cat":"cs.CY","authors_text":"Aadit Kapoor, Donald C. Comeau, Lana Yeganova, Po-Ting Lai, Qiao Jin, Qingqing Zhu, Qingyu Chen, Rezarta Islamaj, Shubo Tian, Won Kim, Xin Gao, Xiuying Chen, Yifan Yang, Zhiyong Lu","submitted_at":"2023-06-15T20:19:08Z","abstract_excerpt":"ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the emergence of diverse applications in the field of biomedicine and health. In this work, we examine the diverse applications of large language models (LLMs), such as ChatGPT, in biomedicine and health. Specifically we explore the areas of biomedical information retrieval, question answering, medical text summarization, information extraction, and medical education, and investigate whether LLMs possess the transformative power"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.10070","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/2306.10070/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":"2026-07-05T07:33:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6AnVER+ruFIWu3CfoGpFxX1Me0OUuVMrx9PZfbwjqNdP+m/buOZtRKN4dLzNv0fEhW4zB2OYMipkUkb5tRRnDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T15:43:18.849881Z"},"content_sha256":"92d78d76962767b8c247903b7a334930ae7e93ca560d13b4124915df62a500e8","schema_version":"1.0","event_id":"sha256:92d78d76962767b8c247903b7a334930ae7e93ca560d13b4124915df62a500e8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B3ABAYYP3EEX65MXJ2KZXMHEEZ/bundle.json","state_url":"https://pith.science/pith/B3ABAYYP3EEX65MXJ2KZXMHEEZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B3ABAYYP3EEX65MXJ2KZXMHEEZ/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":"2026-08-06T15:43:18Z","links":{"resolver":"https://pith.science/pith/B3ABAYYP3EEX65MXJ2KZXMHEEZ","bundle":"https://pith.science/pith/B3ABAYYP3EEX65MXJ2KZXMHEEZ/bundle.json","state":"https://pith.science/pith/B3ABAYYP3EEX65MXJ2KZXMHEEZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B3ABAYYP3EEX65MXJ2KZXMHEEZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:B3ABAYYP3EEX65MXJ2KZXMHEEZ","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":"244922b237d53c8f4514113bc4fe03c8e6748d0168ef306aa775f38283054d6e","cross_cats_sorted":["cs.AI","cs.CL","q-bio.QM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2023-06-15T20:19:08Z","title_canon_sha256":"8ab94364e726da0df209185e1e40e0f03c3c4aad6ec382013c16e19ab4a3ad6b"},"schema_version":"1.0","source":{"id":"2306.10070","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.10070","created_at":"2026-07-05T07:33:17Z"},{"alias_kind":"arxiv_version","alias_value":"2306.10070v2","created_at":"2026-07-05T07:33:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.10070","created_at":"2026-07-05T07:33:17Z"},{"alias_kind":"pith_short_12","alias_value":"B3ABAYYP3EEX","created_at":"2026-07-05T07:33:17Z"},{"alias_kind":"pith_short_16","alias_value":"B3ABAYYP3EEX65MX","created_at":"2026-07-05T07:33:17Z"},{"alias_kind":"pith_short_8","alias_value":"B3ABAYYP","created_at":"2026-07-05T07:33:17Z"}],"graph_snapshots":[{"event_id":"sha256:92d78d76962767b8c247903b7a334930ae7e93ca560d13b4124915df62a500e8","target":"graph","created_at":"2026-07-05T07:33:17Z","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/2306.10070/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the emergence of diverse applications in the field of biomedicine and health. In this work, we examine the diverse applications of large language models (LLMs), such as ChatGPT, in biomedicine and health. Specifically we explore the areas of biomedical information retrieval, question answering, medical text summarization, information extraction, and medical education, and investigate whether LLMs possess the transformative power","authors_text":"Aadit Kapoor, Donald C. Comeau, Lana Yeganova, Po-Ting Lai, Qiao Jin, Qingqing Zhu, Qingyu Chen, Rezarta Islamaj, Shubo Tian, Won Kim, Xin Gao, Xiuying Chen, Yifan Yang, Zhiyong Lu","cross_cats":["cs.AI","cs.CL","q-bio.QM"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2023-06-15T20:19:08Z","title":"Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.10070","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":"sha256:8884e6e5f822323dc54eddd0dee2c096a4f6d9e8db0ec80a06fd7d31a25c48a3","target":"record","created_at":"2026-07-05T07:33:17Z","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":"244922b237d53c8f4514113bc4fe03c8e6748d0168ef306aa775f38283054d6e","cross_cats_sorted":["cs.AI","cs.CL","q-bio.QM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2023-06-15T20:19:08Z","title_canon_sha256":"8ab94364e726da0df209185e1e40e0f03c3c4aad6ec382013c16e19ab4a3ad6b"},"schema_version":"1.0","source":{"id":"2306.10070","kind":"arxiv","version":2}},"canonical_sha256":"0ec010630fd9097f75974e959bb0e4267ac2597ccbeba787d768346a87aa04d2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0ec010630fd9097f75974e959bb0e4267ac2597ccbeba787d768346a87aa04d2","first_computed_at":"2026-07-05T07:33:17.143045Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:33:17.143045Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1Y0Lozg1qoKjZIzCcqoDQDcCRBnUJB1qVSgBFDHT2AGq+Qa9oOkoY0BTKIN4CaE2RXMFzcWZQP0LzitdIW/0Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:33:17.143694Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.10070","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8884e6e5f822323dc54eddd0dee2c096a4f6d9e8db0ec80a06fd7d31a25c48a3","sha256:92d78d76962767b8c247903b7a334930ae7e93ca560d13b4124915df62a500e8"],"state_sha256":"cd0f17a05c80e018f0b45174312736b7164f763421046efb405bf8c39b8d4a63"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zQpqVW2+Qox7Q43dorHOLFwlZLv7+asQrdMVXiVvrlA0XUMzYpuaZsQWNvjq5EJb1GPXxVCBbBo1Ujkyhl7uAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T15:43:18.853776Z","bundle_sha256":"d24425f45be8f0639465f77e119e84a7be8b5da14732ea33b74f0c69ed96a025"}}