{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:YA6XKD45OREMYGDPTNBVCQ45ZS","short_pith_number":"pith:YA6XKD45","canonical_record":{"source":{"id":"2406.09103","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-13T13:31:04Z","cross_cats_sorted":[],"title_canon_sha256":"56931e66b1557af1f212db2acbbdbe02eedddf1424e9c8d2fde7be6beeacd66a","abstract_canon_sha256":"7c29af83460da8c11b29edb912fc867b9d032db76d9f013688dea6f907f62778"},"schema_version":"1.0"},"canonical_sha256":"c03d750f9d7448cc186f9b4351439dcc9ebb1abaccbbc72e00d9b3e3994acaf9","source":{"kind":"arxiv","id":"2406.09103","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.09103","created_at":"2026-07-05T08:31:28Z"},{"alias_kind":"arxiv_version","alias_value":"2406.09103v1","created_at":"2026-07-05T08:31:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.09103","created_at":"2026-07-05T08:31:28Z"},{"alias_kind":"pith_short_12","alias_value":"YA6XKD45OREM","created_at":"2026-07-05T08:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"YA6XKD45OREMYGDP","created_at":"2026-07-05T08:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"YA6XKD45","created_at":"2026-07-05T08:31:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:YA6XKD45OREMYGDPTNBVCQ45ZS","target":"record","payload":{"canonical_record":{"source":{"id":"2406.09103","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-13T13:31:04Z","cross_cats_sorted":[],"title_canon_sha256":"56931e66b1557af1f212db2acbbdbe02eedddf1424e9c8d2fde7be6beeacd66a","abstract_canon_sha256":"7c29af83460da8c11b29edb912fc867b9d032db76d9f013688dea6f907f62778"},"schema_version":"1.0"},"canonical_sha256":"c03d750f9d7448cc186f9b4351439dcc9ebb1abaccbbc72e00d9b3e3994acaf9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:31:28.223344Z","signature_b64":"gYKcVn6rItPyX6WQz3jaWjCCcouvfIt71oeznzLFxXflHva5FAitckezPQgzCEzBLcsGbrgAZG3bC2QFkNCtDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c03d750f9d7448cc186f9b4351439dcc9ebb1abaccbbc72e00d9b3e3994acaf9","last_reissued_at":"2026-07-05T08:31:28.222845Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:31:28.222845Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.09103","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":"2026-07-05T08:31:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DPPPOZPreyxzO6iaRTRsI+vboiZIVRxJG5BEiov0WeHkSUqqJ4e+WbrI9zbWGPeWOSBC9coIyBNPUnJ7HkekAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-25T09:31:30.517755Z"},"content_sha256":"b361b15cce1e65f495112cc8b2761d7b1f5fbf75b5e696f2d1402ea5d4d3a3a4","schema_version":"1.0","event_id":"sha256:b361b15cce1e65f495112cc8b2761d7b1f5fbf75b5e696f2d1402ea5d4d3a3a4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:YA6XKD45OREMYGDPTNBVCQ45ZS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Chain-of-Though (CoT) prompting strategies for medical error detection and correction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Abul Hasan, Honghan Wu, Jason P.Y. Cheung, Jinge Wu, Teng Zhang, Yunsoo Kim, Zhaolong Wu","submitted_at":"2024-06-13T13:31:04Z","abstract_excerpt":"This paper describes our submission to the MEDIQA-CORR 2024 shared task for automatically detecting and correcting medical errors in clinical notes. We report results for three methods of few-shot In-Context Learning (ICL) augmented with Chain-of-Thought (CoT) and reason prompts using a large language model (LLM). In the first method, we manually analyse a subset of train and validation dataset to infer three CoT prompts by examining error types in the clinical notes. In the second method, we utilise the training dataset to prompt the LLM to deduce reasons about their correctness or incorrectn"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.09103","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/2406.09103/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":"2026-07-05T08:31:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e+feKwm77Mxoz/nV6GsGwpA59hrH19vu0VNLXgK5tiykRr9gZE1HFH41+yeI+jHyGLWhviRNGtr0+wNINQJVCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-25T09:31:30.518133Z"},"content_sha256":"eacc091edfead669776b32823cf0ba4c0da3d43c2f12aa90451284a17106c1cf","schema_version":"1.0","event_id":"sha256:eacc091edfead669776b32823cf0ba4c0da3d43c2f12aa90451284a17106c1cf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YA6XKD45OREMYGDPTNBVCQ45ZS/bundle.json","state_url":"https://pith.science/pith/YA6XKD45OREMYGDPTNBVCQ45ZS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YA6XKD45OREMYGDPTNBVCQ45ZS/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":"2026-07-25T09:31:30Z","links":{"resolver":"https://pith.science/pith/YA6XKD45OREMYGDPTNBVCQ45ZS","bundle":"https://pith.science/pith/YA6XKD45OREMYGDPTNBVCQ45ZS/bundle.json","state":"https://pith.science/pith/YA6XKD45OREMYGDPTNBVCQ45ZS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YA6XKD45OREMYGDPTNBVCQ45ZS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:YA6XKD45OREMYGDPTNBVCQ45ZS","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":"7c29af83460da8c11b29edb912fc867b9d032db76d9f013688dea6f907f62778","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-13T13:31:04Z","title_canon_sha256":"56931e66b1557af1f212db2acbbdbe02eedddf1424e9c8d2fde7be6beeacd66a"},"schema_version":"1.0","source":{"id":"2406.09103","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.09103","created_at":"2026-07-05T08:31:28Z"},{"alias_kind":"arxiv_version","alias_value":"2406.09103v1","created_at":"2026-07-05T08:31:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.09103","created_at":"2026-07-05T08:31:28Z"},{"alias_kind":"pith_short_12","alias_value":"YA6XKD45OREM","created_at":"2026-07-05T08:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"YA6XKD45OREMYGDP","created_at":"2026-07-05T08:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"YA6XKD45","created_at":"2026-07-05T08:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:eacc091edfead669776b32823cf0ba4c0da3d43c2f12aa90451284a17106c1cf","target":"graph","created_at":"2026-07-05T08:31:28Z","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/2406.09103/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper describes our submission to the MEDIQA-CORR 2024 shared task for automatically detecting and correcting medical errors in clinical notes. We report results for three methods of few-shot In-Context Learning (ICL) augmented with Chain-of-Thought (CoT) and reason prompts using a large language model (LLM). In the first method, we manually analyse a subset of train and validation dataset to infer three CoT prompts by examining error types in the clinical notes. In the second method, we utilise the training dataset to prompt the LLM to deduce reasons about their correctness or incorrectn","authors_text":"Abul Hasan, Honghan Wu, Jason P.Y. Cheung, Jinge Wu, Teng Zhang, Yunsoo Kim, Zhaolong Wu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-13T13:31:04Z","title":"Chain-of-Though (CoT) prompting strategies for medical error detection and correction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.09103","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:b361b15cce1e65f495112cc8b2761d7b1f5fbf75b5e696f2d1402ea5d4d3a3a4","target":"record","created_at":"2026-07-05T08:31:28Z","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":"7c29af83460da8c11b29edb912fc867b9d032db76d9f013688dea6f907f62778","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-13T13:31:04Z","title_canon_sha256":"56931e66b1557af1f212db2acbbdbe02eedddf1424e9c8d2fde7be6beeacd66a"},"schema_version":"1.0","source":{"id":"2406.09103","kind":"arxiv","version":1}},"canonical_sha256":"c03d750f9d7448cc186f9b4351439dcc9ebb1abaccbbc72e00d9b3e3994acaf9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c03d750f9d7448cc186f9b4351439dcc9ebb1abaccbbc72e00d9b3e3994acaf9","first_computed_at":"2026-07-05T08:31:28.222845Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:31:28.222845Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gYKcVn6rItPyX6WQz3jaWjCCcouvfIt71oeznzLFxXflHva5FAitckezPQgzCEzBLcsGbrgAZG3bC2QFkNCtDA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:31:28.223344Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.09103","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b361b15cce1e65f495112cc8b2761d7b1f5fbf75b5e696f2d1402ea5d4d3a3a4","sha256:eacc091edfead669776b32823cf0ba4c0da3d43c2f12aa90451284a17106c1cf"],"state_sha256":"64c90d9bbdee1e3ecb64a23a8aafbc11dcf80a3ff7040306f000c9a5309512e3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0dmreDt7sPG7wRE9euFN3VRheyh4wSyHF+3vwSDdadQFo9qHQ3aQgqD250sulNNlkPU7B/P6rR/ERoDW0MtFBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-25T09:31:30.520644Z","bundle_sha256":"44695cd70f295e52c8e493075e7169038bd058e93756cdaed8059bf337488325"}}