{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:FELALHQ4UHNLDBOZZQ4UTKPYVK","short_pith_number":"pith:FELALHQ4","canonical_record":{"source":{"id":"2401.11505","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-21T14:30:20Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"9f4243cf7646015167ed59cffda22f96704907d61a2383bcb1424652cf04524e","abstract_canon_sha256":"d9ab9afcb2b850fbb224ea81e82178e17e47db2c77f8ffbede0b423be59e61cc"},"schema_version":"1.0"},"canonical_sha256":"2916059e1ca1dab185d9cc3949a9f8aaa124f1daa533b647059b720afc5e328a","source":{"kind":"arxiv","id":"2401.11505","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.11505","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"arxiv_version","alias_value":"2401.11505v2","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.11505","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_12","alias_value":"FELALHQ4UHNL","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"FELALHQ4UHNLDBOZ","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"FELALHQ4","created_at":"2026-07-05T09:31:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:FELALHQ4UHNLDBOZZQ4UTKPYVK","target":"record","payload":{"canonical_record":{"source":{"id":"2401.11505","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-21T14:30:20Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"9f4243cf7646015167ed59cffda22f96704907d61a2383bcb1424652cf04524e","abstract_canon_sha256":"d9ab9afcb2b850fbb224ea81e82178e17e47db2c77f8ffbede0b423be59e61cc"},"schema_version":"1.0"},"canonical_sha256":"2916059e1ca1dab185d9cc3949a9f8aaa124f1daa533b647059b720afc5e328a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:31:43.230105Z","signature_b64":"VH710h6QtyCSdc3KpBWIMEel9fXRA8Ujn0mb3xkf/YP4sv3VCmsSGmUwOALdIuyBrBM3LNkt+E2HasPIOzFyBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2916059e1ca1dab185d9cc3949a9f8aaa124f1daa533b647059b720afc5e328a","last_reissued_at":"2026-07-05T09:31:43.229636Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:31:43.229636Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.11505","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":"2026-07-05T09:31:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1/O0KOn0S4yX4tYjtodxk/2vq7QRymZwkdkozVPDcC9ZmfyzXhhIzhu/iTAiuE94uFsAkVJ8m5/UPwD2o4JBDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T19:47:02.132553Z"},"content_sha256":"88d6e044b5631dc513f83066f96e4cef2c30ea910f1de1216a1fe4badf524a47","schema_version":"1.0","event_id":"sha256:88d6e044b5631dc513f83066f96e4cef2c30ea910f1de1216a1fe4badf524a47"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:FELALHQ4UHNLDBOZZQ4UTKPYVK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CheX-GPT: Harnessing Large Language Models for Enhanced Chest X-ray Report Labeling","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CL","authors_text":"Byungseok Roh, Eun Kyoung Hong, Han-Cheol Cho, Jawook Gu, Jiho Kim, Kihyun You","submitted_at":"2024-01-21T14:30:20Z","abstract_excerpt":"Free-text radiology reports present a rich data source for various medical tasks, but effectively labeling these texts remains challenging. Traditional rule-based labeling methods fall short of capturing the nuances of diverse free-text patterns. Moreover, models using expert-annotated data are limited by data scarcity and pre-defined classes, impacting their performance, flexibility and scalability. To address these issues, our study offers three main contributions: 1) We demonstrate the potential of GPT as an adept labeler using carefully designed prompts. 2) Utilizing only the data labeled "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.11505","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/2401.11505/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":"2026-07-05T09:31:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SRi9pxiK79K/eKZBszOqQqg8Ej4h3eGLlkWXr2vBcSv0U/IWOy19ULMof9c9IHn7bYnvBNEqPI8c6tSv2sTHCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T19:47:02.133139Z"},"content_sha256":"465bafc2b2c4032ea3e79e3a6662949eb3d0fbf181699a701b9da98b8c64cbe8","schema_version":"1.0","event_id":"sha256:465bafc2b2c4032ea3e79e3a6662949eb3d0fbf181699a701b9da98b8c64cbe8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FELALHQ4UHNLDBOZZQ4UTKPYVK/bundle.json","state_url":"https://pith.science/pith/FELALHQ4UHNLDBOZZQ4UTKPYVK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FELALHQ4UHNLDBOZZQ4UTKPYVK/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":"2026-08-09T19:47:02Z","links":{"resolver":"https://pith.science/pith/FELALHQ4UHNLDBOZZQ4UTKPYVK","bundle":"https://pith.science/pith/FELALHQ4UHNLDBOZZQ4UTKPYVK/bundle.json","state":"https://pith.science/pith/FELALHQ4UHNLDBOZZQ4UTKPYVK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FELALHQ4UHNLDBOZZQ4UTKPYVK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:FELALHQ4UHNLDBOZZQ4UTKPYVK","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":"d9ab9afcb2b850fbb224ea81e82178e17e47db2c77f8ffbede0b423be59e61cc","cross_cats_sorted":["cs.IR"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-21T14:30:20Z","title_canon_sha256":"9f4243cf7646015167ed59cffda22f96704907d61a2383bcb1424652cf04524e"},"schema_version":"1.0","source":{"id":"2401.11505","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.11505","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"arxiv_version","alias_value":"2401.11505v2","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.11505","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_12","alias_value":"FELALHQ4UHNL","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"FELALHQ4UHNLDBOZ","created_at":"2026-07-05T09:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"FELALHQ4","created_at":"2026-07-05T09:31:43Z"}],"graph_snapshots":[{"event_id":"sha256:465bafc2b2c4032ea3e79e3a6662949eb3d0fbf181699a701b9da98b8c64cbe8","target":"graph","created_at":"2026-07-05T09:31:43Z","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/2401.11505/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Free-text radiology reports present a rich data source for various medical tasks, but effectively labeling these texts remains challenging. Traditional rule-based labeling methods fall short of capturing the nuances of diverse free-text patterns. Moreover, models using expert-annotated data are limited by data scarcity and pre-defined classes, impacting their performance, flexibility and scalability. To address these issues, our study offers three main contributions: 1) We demonstrate the potential of GPT as an adept labeler using carefully designed prompts. 2) Utilizing only the data labeled ","authors_text":"Byungseok Roh, Eun Kyoung Hong, Han-Cheol Cho, Jawook Gu, Jiho Kim, Kihyun You","cross_cats":["cs.IR"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-21T14:30:20Z","title":"CheX-GPT: Harnessing Large Language Models for Enhanced Chest X-ray Report Labeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.11505","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":"sha256:88d6e044b5631dc513f83066f96e4cef2c30ea910f1de1216a1fe4badf524a47","target":"record","created_at":"2026-07-05T09:31:43Z","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":"d9ab9afcb2b850fbb224ea81e82178e17e47db2c77f8ffbede0b423be59e61cc","cross_cats_sorted":["cs.IR"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-21T14:30:20Z","title_canon_sha256":"9f4243cf7646015167ed59cffda22f96704907d61a2383bcb1424652cf04524e"},"schema_version":"1.0","source":{"id":"2401.11505","kind":"arxiv","version":2}},"canonical_sha256":"2916059e1ca1dab185d9cc3949a9f8aaa124f1daa533b647059b720afc5e328a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2916059e1ca1dab185d9cc3949a9f8aaa124f1daa533b647059b720afc5e328a","first_computed_at":"2026-07-05T09:31:43.229636Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:31:43.229636Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VH710h6QtyCSdc3KpBWIMEel9fXRA8Ujn0mb3xkf/YP4sv3VCmsSGmUwOALdIuyBrBM3LNkt+E2HasPIOzFyBA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:31:43.230105Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.11505","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:88d6e044b5631dc513f83066f96e4cef2c30ea910f1de1216a1fe4badf524a47","sha256:465bafc2b2c4032ea3e79e3a6662949eb3d0fbf181699a701b9da98b8c64cbe8"],"state_sha256":"5ab6c61ed6b99dc1de2feca2dbd3bdab4340f9c0102e7ee0c75bcfd062b1696a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ke+eIl5k0TpfaAk4nHZ0Ry0p+MXL8mFwkn8bjzvcA2z2a5k2ghTWWmK7p9L6NennJAPbPSWj+cwYNZtXTxmkCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T19:47:02.136461Z","bundle_sha256":"66c22925d8264c213cd729cc5032f14bdb1332481ce310c9d7338646ae822fd9"}}