{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GXKY5MFOBPYU3NKOGI7O5XI3KS","short_pith_number":"pith:GXKY5MFO","canonical_record":{"source":{"id":"2410.15828","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-21T09:46:37Z","cross_cats_sorted":[],"title_canon_sha256":"bbb67654804eb60274c42f4491086d7df49239b487441a1e422dd857392b35ae","abstract_canon_sha256":"04f09b32ad812a9a1e792921a9270bda9169e06d3d9f437fb89d3264021686aa"},"schema_version":"1.0"},"canonical_sha256":"35d58eb0ae0bf14db54e323eeedd1b54a0d023086df8a074450bbb33a315bf93","source":{"kind":"arxiv","id":"2410.15828","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.15828","created_at":"2026-07-05T09:23:25Z"},{"alias_kind":"arxiv_version","alias_value":"2410.15828v1","created_at":"2026-07-05T09:23:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.15828","created_at":"2026-07-05T09:23:25Z"},{"alias_kind":"pith_short_12","alias_value":"GXKY5MFOBPYU","created_at":"2026-07-05T09:23:25Z"},{"alias_kind":"pith_short_16","alias_value":"GXKY5MFOBPYU3NKO","created_at":"2026-07-05T09:23:25Z"},{"alias_kind":"pith_short_8","alias_value":"GXKY5MFO","created_at":"2026-07-05T09:23:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GXKY5MFOBPYU3NKOGI7O5XI3KS","target":"record","payload":{"canonical_record":{"source":{"id":"2410.15828","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-21T09:46:37Z","cross_cats_sorted":[],"title_canon_sha256":"bbb67654804eb60274c42f4491086d7df49239b487441a1e422dd857392b35ae","abstract_canon_sha256":"04f09b32ad812a9a1e792921a9270bda9169e06d3d9f437fb89d3264021686aa"},"schema_version":"1.0"},"canonical_sha256":"35d58eb0ae0bf14db54e323eeedd1b54a0d023086df8a074450bbb33a315bf93","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:23:25.500895Z","signature_b64":"TkeWZvdaU2s1/HPD/P58hRcMTa5JxoRyuyjbQPneRVYs3g2pSD2cSQrmPrg6yaxR1CRshc2iGtVq/bXFz7sfDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"35d58eb0ae0bf14db54e323eeedd1b54a0d023086df8a074450bbb33a315bf93","last_reissued_at":"2026-07-05T09:23:25.500372Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:23:25.500372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.15828","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":"2026-07-05T09:23:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DZ+NfhAb4QXNQ/2Yq43IxQM9Z8OgJd6n9rjHMqlFOhvOETcffW7Ssc/JDZmkzo9u6hzGMBYsWz75GzhErhDaBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T10:16:18.124954Z"},"content_sha256":"7320ccf58530e9a7774bb508116c1a881f0b67fdf932717252d563db4ac0a081","schema_version":"1.0","event_id":"sha256:7320ccf58530e9a7774bb508116c1a881f0b67fdf932717252d563db4ac0a081"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GXKY5MFOBPYU3NKOGI7O5XI3KS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs -- Evaluation through Synthetic Data Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Ivaxi Sheth, Mario Fritz, Matthias Becker, Ruta Binkyte, Tejumade Afonja, Thomas Ulas, Waqar Hanif","submitted_at":"2024-10-21T09:46:37Z","abstract_excerpt":"Gene regulatory networks (GRNs) represent the causal relationships between transcription factors (TFs) and target genes in single-cell RNA sequencing (scRNA-seq) data. Understanding these networks is crucial for uncovering disease mechanisms and identifying therapeutic targets. In this work, we investigate the potential of large language models (LLMs) for GRN discovery, leveraging their learned biological knowledge alone or in combination with traditional statistical methods. We develop a task-based evaluation strategy to address the challenge of unavailable ground truth causal graphs. Specifi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.15828","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/2410.15828/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":"2026-07-05T09:23:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NqGHzDATwqKniJrViQZy1bFMQiPK+1s+nLmXEqGqdYx/9C9tsDAXJeAVst8lE0tg66L51EfSgw277UL3xPrGBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T10:16:18.125909Z"},"content_sha256":"7a1cee678741bd5bacad5c4787fc924016cdadce817ef81ab40bcc8322e91ff2","schema_version":"1.0","event_id":"sha256:7a1cee678741bd5bacad5c4787fc924016cdadce817ef81ab40bcc8322e91ff2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GXKY5MFOBPYU3NKOGI7O5XI3KS/bundle.json","state_url":"https://pith.science/pith/GXKY5MFOBPYU3NKOGI7O5XI3KS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GXKY5MFOBPYU3NKOGI7O5XI3KS/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":"2026-08-10T10:16:18Z","links":{"resolver":"https://pith.science/pith/GXKY5MFOBPYU3NKOGI7O5XI3KS","bundle":"https://pith.science/pith/GXKY5MFOBPYU3NKOGI7O5XI3KS/bundle.json","state":"https://pith.science/pith/GXKY5MFOBPYU3NKOGI7O5XI3KS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GXKY5MFOBPYU3NKOGI7O5XI3KS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GXKY5MFOBPYU3NKOGI7O5XI3KS","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":"04f09b32ad812a9a1e792921a9270bda9169e06d3d9f437fb89d3264021686aa","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-21T09:46:37Z","title_canon_sha256":"bbb67654804eb60274c42f4491086d7df49239b487441a1e422dd857392b35ae"},"schema_version":"1.0","source":{"id":"2410.15828","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.15828","created_at":"2026-07-05T09:23:25Z"},{"alias_kind":"arxiv_version","alias_value":"2410.15828v1","created_at":"2026-07-05T09:23:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.15828","created_at":"2026-07-05T09:23:25Z"},{"alias_kind":"pith_short_12","alias_value":"GXKY5MFOBPYU","created_at":"2026-07-05T09:23:25Z"},{"alias_kind":"pith_short_16","alias_value":"GXKY5MFOBPYU3NKO","created_at":"2026-07-05T09:23:25Z"},{"alias_kind":"pith_short_8","alias_value":"GXKY5MFO","created_at":"2026-07-05T09:23:25Z"}],"graph_snapshots":[{"event_id":"sha256:7a1cee678741bd5bacad5c4787fc924016cdadce817ef81ab40bcc8322e91ff2","target":"graph","created_at":"2026-07-05T09:23:25Z","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/2410.15828/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Gene regulatory networks (GRNs) represent the causal relationships between transcription factors (TFs) and target genes in single-cell RNA sequencing (scRNA-seq) data. Understanding these networks is crucial for uncovering disease mechanisms and identifying therapeutic targets. In this work, we investigate the potential of large language models (LLMs) for GRN discovery, leveraging their learned biological knowledge alone or in combination with traditional statistical methods. We develop a task-based evaluation strategy to address the challenge of unavailable ground truth causal graphs. Specifi","authors_text":"Ivaxi Sheth, Mario Fritz, Matthias Becker, Ruta Binkyte, Tejumade Afonja, Thomas Ulas, Waqar Hanif","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-21T09:46:37Z","title":"LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs -- Evaluation through Synthetic Data Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.15828","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":"sha256:7320ccf58530e9a7774bb508116c1a881f0b67fdf932717252d563db4ac0a081","target":"record","created_at":"2026-07-05T09:23:25Z","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":"04f09b32ad812a9a1e792921a9270bda9169e06d3d9f437fb89d3264021686aa","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-21T09:46:37Z","title_canon_sha256":"bbb67654804eb60274c42f4491086d7df49239b487441a1e422dd857392b35ae"},"schema_version":"1.0","source":{"id":"2410.15828","kind":"arxiv","version":1}},"canonical_sha256":"35d58eb0ae0bf14db54e323eeedd1b54a0d023086df8a074450bbb33a315bf93","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"35d58eb0ae0bf14db54e323eeedd1b54a0d023086df8a074450bbb33a315bf93","first_computed_at":"2026-07-05T09:23:25.500372Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:23:25.500372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TkeWZvdaU2s1/HPD/P58hRcMTa5JxoRyuyjbQPneRVYs3g2pSD2cSQrmPrg6yaxR1CRshc2iGtVq/bXFz7sfDA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:23:25.500895Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.15828","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7320ccf58530e9a7774bb508116c1a881f0b67fdf932717252d563db4ac0a081","sha256:7a1cee678741bd5bacad5c4787fc924016cdadce817ef81ab40bcc8322e91ff2"],"state_sha256":"fb40cbc0d3a3a15c7de5ce6fbb478d410e637a6b56d596ad305ad74f3a7a6ee2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O+miJ2bNqkSk37ruXNYa1BgQW6CQBT1wsHjEFe7E/yT9uPwIimHMzOucSwjxzu4hNgS4TjNSgfHz94ATjkjrAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T10:16:18.131560Z","bundle_sha256":"fd998a00dba85ffa44d77b42f54830559ba616982bcbe99057f93354631df336"}}