{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:UIFYV3AZN3D3CIAZQU3BLGB5HN","short_pith_number":"pith:UIFYV3AZ","canonical_record":{"source":{"id":"2404.16659","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-25T14:55:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"a6b20b712df129830f5f318e5c9b8610cbbfa3cde72abe0dc4235c195ddf819b","abstract_canon_sha256":"929c1b9fccd52266a49883fe1f17f6208ebf59f99a0d9a83729ca6ea81485f58"},"schema_version":"1.0"},"canonical_sha256":"a20b8aec196ec7b12019853615983d3b4a893b8819408f4a948e48922d83dd57","source":{"kind":"arxiv","id":"2404.16659","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.16659","created_at":"2026-07-05T08:12:11Z"},{"alias_kind":"arxiv_version","alias_value":"2404.16659v1","created_at":"2026-07-05T08:12:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.16659","created_at":"2026-07-05T08:12:11Z"},{"alias_kind":"pith_short_12","alias_value":"UIFYV3AZN3D3","created_at":"2026-07-05T08:12:11Z"},{"alias_kind":"pith_short_16","alias_value":"UIFYV3AZN3D3CIAZ","created_at":"2026-07-05T08:12:11Z"},{"alias_kind":"pith_short_8","alias_value":"UIFYV3AZ","created_at":"2026-07-05T08:12:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:UIFYV3AZN3D3CIAZQU3BLGB5HN","target":"record","payload":{"canonical_record":{"source":{"id":"2404.16659","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-25T14:55:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"a6b20b712df129830f5f318e5c9b8610cbbfa3cde72abe0dc4235c195ddf819b","abstract_canon_sha256":"929c1b9fccd52266a49883fe1f17f6208ebf59f99a0d9a83729ca6ea81485f58"},"schema_version":"1.0"},"canonical_sha256":"a20b8aec196ec7b12019853615983d3b4a893b8819408f4a948e48922d83dd57","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:12:11.138658Z","signature_b64":"d/1qjgmyy9XcQ9aU30g9m4v8ow8Xebp/3zwbrghTc41D1H4yOA/PVlc/dpZc+hH2nMdrqy/IbFMtXNgMCHb6CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a20b8aec196ec7b12019853615983d3b4a893b8819408f4a948e48922d83dd57","last_reissued_at":"2026-07-05T08:12:11.138056Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:12:11.138056Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.16659","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":"2026-07-05T08:12:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7wN9Yrb2FG5pErWep38aT7c7kchatzazMDpeG9+1qaXOVB4aIU8Swd61DMzHxbGpjM+Shp+JIi29wB/TFj5ODw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T06:18:53.917941Z"},"content_sha256":"8f87430cc3e77f969f3916ef81b299f546871f253275c9ba33fc03d8e4479064","schema_version":"1.0","event_id":"sha256:8f87430cc3e77f969f3916ef81b299f546871f253275c9ba33fc03d8e4479064"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:UIFYV3AZN3D3CIAZQU3BLGB5HN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ProbGate at EHRSQL 2024: Enhancing SQL Query Generation Accuracy through Probabilistic Threshold Filtering and Error Handling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Donghee Han, Sangryul Kim, Sehyun Kim","submitted_at":"2024-04-25T14:55:07Z","abstract_excerpt":"Recently, deep learning-based language models have significantly enhanced text-to-SQL tasks, with promising applications in retrieving patient records within the medical domain. One notable challenge in such applications is discerning unanswerable queries. Through fine-tuning model, we demonstrate the feasibility of converting medical record inquiries into SQL queries. Additionally, we introduce an entropy-based method to identify and filter out unanswerable results. We further enhance result quality by filtering low-confidence SQL through log probability-based distribution, while grammatical "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.16659","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/2404.16659/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":"2026-07-05T08:12:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EP6pXR+hJJeQmX7HninO0miRabmXyc48LytVBf/MDVyqHgAi+Owk3A5lSDni+rbP72U9Y/R9Yo6TzRP8C8ttBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T06:18:53.918465Z"},"content_sha256":"9a234f433033fa20f3503685f4110dc824d697fac63a6ab8c228f2a4fa87401b","schema_version":"1.0","event_id":"sha256:9a234f433033fa20f3503685f4110dc824d697fac63a6ab8c228f2a4fa87401b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UIFYV3AZN3D3CIAZQU3BLGB5HN/bundle.json","state_url":"https://pith.science/pith/UIFYV3AZN3D3CIAZQU3BLGB5HN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UIFYV3AZN3D3CIAZQU3BLGB5HN/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":"2026-08-23T06:18:53Z","links":{"resolver":"https://pith.science/pith/UIFYV3AZN3D3CIAZQU3BLGB5HN","bundle":"https://pith.science/pith/UIFYV3AZN3D3CIAZQU3BLGB5HN/bundle.json","state":"https://pith.science/pith/UIFYV3AZN3D3CIAZQU3BLGB5HN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UIFYV3AZN3D3CIAZQU3BLGB5HN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:UIFYV3AZN3D3CIAZQU3BLGB5HN","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":"929c1b9fccd52266a49883fe1f17f6208ebf59f99a0d9a83729ca6ea81485f58","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-25T14:55:07Z","title_canon_sha256":"a6b20b712df129830f5f318e5c9b8610cbbfa3cde72abe0dc4235c195ddf819b"},"schema_version":"1.0","source":{"id":"2404.16659","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.16659","created_at":"2026-07-05T08:12:11Z"},{"alias_kind":"arxiv_version","alias_value":"2404.16659v1","created_at":"2026-07-05T08:12:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.16659","created_at":"2026-07-05T08:12:11Z"},{"alias_kind":"pith_short_12","alias_value":"UIFYV3AZN3D3","created_at":"2026-07-05T08:12:11Z"},{"alias_kind":"pith_short_16","alias_value":"UIFYV3AZN3D3CIAZ","created_at":"2026-07-05T08:12:11Z"},{"alias_kind":"pith_short_8","alias_value":"UIFYV3AZ","created_at":"2026-07-05T08:12:11Z"}],"graph_snapshots":[{"event_id":"sha256:9a234f433033fa20f3503685f4110dc824d697fac63a6ab8c228f2a4fa87401b","target":"graph","created_at":"2026-07-05T08:12:11Z","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/2404.16659/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, deep learning-based language models have significantly enhanced text-to-SQL tasks, with promising applications in retrieving patient records within the medical domain. One notable challenge in such applications is discerning unanswerable queries. Through fine-tuning model, we demonstrate the feasibility of converting medical record inquiries into SQL queries. Additionally, we introduce an entropy-based method to identify and filter out unanswerable results. We further enhance result quality by filtering low-confidence SQL through log probability-based distribution, while grammatical ","authors_text":"Donghee Han, Sangryul Kim, Sehyun Kim","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-25T14:55:07Z","title":"ProbGate at EHRSQL 2024: Enhancing SQL Query Generation Accuracy through Probabilistic Threshold Filtering and Error Handling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.16659","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":"sha256:8f87430cc3e77f969f3916ef81b299f546871f253275c9ba33fc03d8e4479064","target":"record","created_at":"2026-07-05T08:12:11Z","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":"929c1b9fccd52266a49883fe1f17f6208ebf59f99a0d9a83729ca6ea81485f58","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-04-25T14:55:07Z","title_canon_sha256":"a6b20b712df129830f5f318e5c9b8610cbbfa3cde72abe0dc4235c195ddf819b"},"schema_version":"1.0","source":{"id":"2404.16659","kind":"arxiv","version":1}},"canonical_sha256":"a20b8aec196ec7b12019853615983d3b4a893b8819408f4a948e48922d83dd57","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a20b8aec196ec7b12019853615983d3b4a893b8819408f4a948e48922d83dd57","first_computed_at":"2026-07-05T08:12:11.138056Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:12:11.138056Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"d/1qjgmyy9XcQ9aU30g9m4v8ow8Xebp/3zwbrghTc41D1H4yOA/PVlc/dpZc+hH2nMdrqy/IbFMtXNgMCHb6CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:12:11.138658Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.16659","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8f87430cc3e77f969f3916ef81b299f546871f253275c9ba33fc03d8e4479064","sha256:9a234f433033fa20f3503685f4110dc824d697fac63a6ab8c228f2a4fa87401b"],"state_sha256":"653977260ee3215c7c5a3342d0e208ee8794b72a3307668c4c1cfebc0c1bc004"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aKAyPLPhXvrlOsGk0RnVYKvYvYTaHnc3uAX9JFmluS5gckQr2WCchbG+f/q67XOmntfR5x7rYflngVB/NJvLAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T06:18:53.923603Z","bundle_sha256":"17046eea4508744a05daa13c0f12a950fd180bfba5ed47d1ef7f0eb008769be2"}}