{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:W4MDGY5NDR5UNEDRKRGETUJGTT","short_pith_number":"pith:W4MDGY5N","canonical_record":{"source":{"id":"2306.07297","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-10T20:55:21Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"9264de6c8523a11a574940bb8434f57cda828b485f8cb8f6d1cc6f09368296d2","abstract_canon_sha256":"89856d0144a4d6cb9b5aa54c215c8387dc831e1a2ff34da8bf9c13922dc6ddd9"},"schema_version":"1.0"},"canonical_sha256":"b7183363ad1c7b469071544c49d1269cd123be0b44f2c681ed02d123b964d7e5","source":{"kind":"arxiv","id":"2306.07297","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.07297","created_at":"2026-07-05T06:20:02Z"},{"alias_kind":"arxiv_version","alias_value":"2306.07297v1","created_at":"2026-07-05T06:20:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.07297","created_at":"2026-07-05T06:20:02Z"},{"alias_kind":"pith_short_12","alias_value":"W4MDGY5NDR5U","created_at":"2026-07-05T06:20:02Z"},{"alias_kind":"pith_short_16","alias_value":"W4MDGY5NDR5UNEDR","created_at":"2026-07-05T06:20:02Z"},{"alias_kind":"pith_short_8","alias_value":"W4MDGY5N","created_at":"2026-07-05T06:20:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:W4MDGY5NDR5UNEDRKRGETUJGTT","target":"record","payload":{"canonical_record":{"source":{"id":"2306.07297","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-10T20:55:21Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"9264de6c8523a11a574940bb8434f57cda828b485f8cb8f6d1cc6f09368296d2","abstract_canon_sha256":"89856d0144a4d6cb9b5aa54c215c8387dc831e1a2ff34da8bf9c13922dc6ddd9"},"schema_version":"1.0"},"canonical_sha256":"b7183363ad1c7b469071544c49d1269cd123be0b44f2c681ed02d123b964d7e5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:20:02.103336Z","signature_b64":"fi0Q0AgfzF2PyRrPIa45FZAqSCsAcgcUqEDSmSFGlgIG1fFhVlBMjXK8PXUVTymcZIIemlStPNNA2JQvREcgDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7183363ad1c7b469071544c49d1269cd123be0b44f2c681ed02d123b964d7e5","last_reissued_at":"2026-07-05T06:20:02.102887Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:20:02.102887Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.07297","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":"2026-07-05T06:20:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OOUzfPt9s0szYEgyJ3pOYwoTbwlHuTsvd39am5iGSNtD3Cc4vDj1ZnG5kiJx4iUIKI5lHWNLbksCc1nCAEZSCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T07:06:51.422599Z"},"content_sha256":"ebcbc7fd272609d08c5451875c069245a21bdfd630c4977cdfc44e6356933fc6","schema_version":"1.0","event_id":"sha256:ebcbc7fd272609d08c5451875c069245a21bdfd630c4977cdfc44e6356933fc6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:W4MDGY5NDR5UNEDRKRGETUJGTT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Medical Data Augmentation via ChatGPT: A Case Study on Medication Identification and Medication Event Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Lijun Qian, Shouvon Sarker, Xishuang Dong","submitted_at":"2023-06-10T20:55:21Z","abstract_excerpt":"The identification of key factors such as medications, diseases, and relationships within electronic health records and clinical notes has a wide range of applications in the clinical field. In the N2C2 2022 competitions, various tasks were presented to promote the identification of key factors in electronic health records (EHRs) using the Contextualized Medication Event Dataset (CMED). Pretrained large language models (LLMs) demonstrated exceptional performance in these tasks. This study aims to explore the utilization of LLMs, specifically ChatGPT, for data augmentation to overcome the limit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.07297","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/2306.07297/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":"2026-07-05T06:20:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XrlG3gZqI8LBFbLRArVcD+mh8VZ3lcoEpOgbrHqt49vnlgKE58aJOXo/5IJ0OxKQWXw5jc4P6IXqokekxxkiBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T07:06:51.423594Z"},"content_sha256":"855cef1f84015964ab1a29e4a6aaf7e4bb6c8ba30eafdcc768556f3763cd45b8","schema_version":"1.0","event_id":"sha256:855cef1f84015964ab1a29e4a6aaf7e4bb6c8ba30eafdcc768556f3763cd45b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W4MDGY5NDR5UNEDRKRGETUJGTT/bundle.json","state_url":"https://pith.science/pith/W4MDGY5NDR5UNEDRKRGETUJGTT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W4MDGY5NDR5UNEDRKRGETUJGTT/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":"2026-08-13T07:06:51Z","links":{"resolver":"https://pith.science/pith/W4MDGY5NDR5UNEDRKRGETUJGTT","bundle":"https://pith.science/pith/W4MDGY5NDR5UNEDRKRGETUJGTT/bundle.json","state":"https://pith.science/pith/W4MDGY5NDR5UNEDRKRGETUJGTT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W4MDGY5NDR5UNEDRKRGETUJGTT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:W4MDGY5NDR5UNEDRKRGETUJGTT","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":"89856d0144a4d6cb9b5aa54c215c8387dc831e1a2ff34da8bf9c13922dc6ddd9","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-10T20:55:21Z","title_canon_sha256":"9264de6c8523a11a574940bb8434f57cda828b485f8cb8f6d1cc6f09368296d2"},"schema_version":"1.0","source":{"id":"2306.07297","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.07297","created_at":"2026-07-05T06:20:02Z"},{"alias_kind":"arxiv_version","alias_value":"2306.07297v1","created_at":"2026-07-05T06:20:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.07297","created_at":"2026-07-05T06:20:02Z"},{"alias_kind":"pith_short_12","alias_value":"W4MDGY5NDR5U","created_at":"2026-07-05T06:20:02Z"},{"alias_kind":"pith_short_16","alias_value":"W4MDGY5NDR5UNEDR","created_at":"2026-07-05T06:20:02Z"},{"alias_kind":"pith_short_8","alias_value":"W4MDGY5N","created_at":"2026-07-05T06:20:02Z"}],"graph_snapshots":[{"event_id":"sha256:855cef1f84015964ab1a29e4a6aaf7e4bb6c8ba30eafdcc768556f3763cd45b8","target":"graph","created_at":"2026-07-05T06:20:02Z","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/2306.07297/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The identification of key factors such as medications, diseases, and relationships within electronic health records and clinical notes has a wide range of applications in the clinical field. In the N2C2 2022 competitions, various tasks were presented to promote the identification of key factors in electronic health records (EHRs) using the Contextualized Medication Event Dataset (CMED). Pretrained large language models (LLMs) demonstrated exceptional performance in these tasks. This study aims to explore the utilization of LLMs, specifically ChatGPT, for data augmentation to overcome the limit","authors_text":"Lijun Qian, Shouvon Sarker, Xishuang Dong","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-10T20:55:21Z","title":"Medical Data Augmentation via ChatGPT: A Case Study on Medication Identification and Medication Event Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.07297","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:ebcbc7fd272609d08c5451875c069245a21bdfd630c4977cdfc44e6356933fc6","target":"record","created_at":"2026-07-05T06:20:02Z","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":"89856d0144a4d6cb9b5aa54c215c8387dc831e1a2ff34da8bf9c13922dc6ddd9","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-10T20:55:21Z","title_canon_sha256":"9264de6c8523a11a574940bb8434f57cda828b485f8cb8f6d1cc6f09368296d2"},"schema_version":"1.0","source":{"id":"2306.07297","kind":"arxiv","version":1}},"canonical_sha256":"b7183363ad1c7b469071544c49d1269cd123be0b44f2c681ed02d123b964d7e5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7183363ad1c7b469071544c49d1269cd123be0b44f2c681ed02d123b964d7e5","first_computed_at":"2026-07-05T06:20:02.102887Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:20:02.102887Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fi0Q0AgfzF2PyRrPIa45FZAqSCsAcgcUqEDSmSFGlgIG1fFhVlBMjXK8PXUVTymcZIIemlStPNNA2JQvREcgDg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:20:02.103336Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.07297","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ebcbc7fd272609d08c5451875c069245a21bdfd630c4977cdfc44e6356933fc6","sha256:855cef1f84015964ab1a29e4a6aaf7e4bb6c8ba30eafdcc768556f3763cd45b8"],"state_sha256":"45b381d574db4da76849647b9e161458fea61c71e0059c88fd3125039dc9489b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2Om3uIkn4vjFQbgBwWbvT9IZZqVcKdGTFY0+HOHsEybcTA6WxURTcatCLnK0yr+0B4FvXLO1N7Bp5MHSLs48Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T07:06:51.523501Z","bundle_sha256":"3a065047f3189414a121ab10d456578b9f7f0be8e0f57ab5cb1e4e8c79ea5c5b"}}