{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:K4MVO3GCR4CD3F2OVDETEITZAS","short_pith_number":"pith:K4MVO3GC","canonical_record":{"source":{"id":"2410.20428","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-27T12:52:52Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6f75b3f64ea4012a5ba3bf0c77aa50f6eca4d7a0bc0bd70d4de11442ef10b0bc","abstract_canon_sha256":"c961b12f7dae35fe18ecce1d3826fb40290e3e5073ee7b5b731aacdd0d43e85a"},"schema_version":"1.0"},"canonical_sha256":"5719576cc28f043d974ea8c932227904a1db3f23987d4baa943cfd52890a0c3a","source":{"kind":"arxiv","id":"2410.20428","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.20428","created_at":"2026-07-05T09:26:44Z"},{"alias_kind":"arxiv_version","alias_value":"2410.20428v1","created_at":"2026-07-05T09:26:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.20428","created_at":"2026-07-05T09:26:44Z"},{"alias_kind":"pith_short_12","alias_value":"K4MVO3GCR4CD","created_at":"2026-07-05T09:26:44Z"},{"alias_kind":"pith_short_16","alias_value":"K4MVO3GCR4CD3F2O","created_at":"2026-07-05T09:26:44Z"},{"alias_kind":"pith_short_8","alias_value":"K4MVO3GC","created_at":"2026-07-05T09:26:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:K4MVO3GCR4CD3F2OVDETEITZAS","target":"record","payload":{"canonical_record":{"source":{"id":"2410.20428","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-27T12:52:52Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6f75b3f64ea4012a5ba3bf0c77aa50f6eca4d7a0bc0bd70d4de11442ef10b0bc","abstract_canon_sha256":"c961b12f7dae35fe18ecce1d3826fb40290e3e5073ee7b5b731aacdd0d43e85a"},"schema_version":"1.0"},"canonical_sha256":"5719576cc28f043d974ea8c932227904a1db3f23987d4baa943cfd52890a0c3a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:26:44.751012Z","signature_b64":"h40n3GhyzD1A2fAqs9jTK1z1WPF7sckVfuAY9yOzt40eJS8BXGnXNBvRu4Muzi3eFnyXtyFuZoaOAk4f91EnBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5719576cc28f043d974ea8c932227904a1db3f23987d4baa943cfd52890a0c3a","last_reissued_at":"2026-07-05T09:26:44.750510Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:26:44.750510Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.20428","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":"2026-07-05T09:26:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X2YiuF/VqPWiXyRXj0K0KaZpI8+lY0KnhzMPVAt1MaNetNm1aAT2s2wv2qtB4xCNHs0D1fbBv2rug69IL23yCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T20:01:27.758333Z"},"content_sha256":"6863f47a696696a5724df5b615976542b3d541e4c4db4b79baf2696a5887ee4d","schema_version":"1.0","event_id":"sha256:6863f47a696696a5724df5b615976542b3d541e4c4db4b79baf2696a5887ee4d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:K4MVO3GCR4CD3F2OVDETEITZAS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MedGo: A Chinese Medical Large Language Model","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Bo An, Haitao Zhang","submitted_at":"2024-10-27T12:52:52Z","abstract_excerpt":"Large models are a hot research topic in the field of artificial intelligence. Leveraging their generative capabilities has the potential to enhance the level and quality of medical services. In response to the limitations of current large language models, which often struggle with accuracy and have narrow capabilities in medical applications, this paper presents a Chinese medical large language model, MedGo. MedGo was trained using a combination of high quality unsupervised medical data, supervised data, and preference alignment data, aimed at enhancing both its versatility and precision in m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.20428","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/2410.20428/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":"2026-07-05T09:26:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y+d6gV2dAM1OxoJZH8HbuO4JQl2zT5zhAmiTI3bUTwy3/36kNyG5FhZucLVV6UnPplbfCmZpLgB28nUID76bBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T20:01:27.759024Z"},"content_sha256":"39fe5cb32a0c7f75dff7722621d254232a5013758ada631b35cf5c263bdb099b","schema_version":"1.0","event_id":"sha256:39fe5cb32a0c7f75dff7722621d254232a5013758ada631b35cf5c263bdb099b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/K4MVO3GCR4CD3F2OVDETEITZAS/bundle.json","state_url":"https://pith.science/pith/K4MVO3GCR4CD3F2OVDETEITZAS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/K4MVO3GCR4CD3F2OVDETEITZAS/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":"2026-08-10T20:01:27Z","links":{"resolver":"https://pith.science/pith/K4MVO3GCR4CD3F2OVDETEITZAS","bundle":"https://pith.science/pith/K4MVO3GCR4CD3F2OVDETEITZAS/bundle.json","state":"https://pith.science/pith/K4MVO3GCR4CD3F2OVDETEITZAS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/K4MVO3GCR4CD3F2OVDETEITZAS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:K4MVO3GCR4CD3F2OVDETEITZAS","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":"c961b12f7dae35fe18ecce1d3826fb40290e3e5073ee7b5b731aacdd0d43e85a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-27T12:52:52Z","title_canon_sha256":"6f75b3f64ea4012a5ba3bf0c77aa50f6eca4d7a0bc0bd70d4de11442ef10b0bc"},"schema_version":"1.0","source":{"id":"2410.20428","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.20428","created_at":"2026-07-05T09:26:44Z"},{"alias_kind":"arxiv_version","alias_value":"2410.20428v1","created_at":"2026-07-05T09:26:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.20428","created_at":"2026-07-05T09:26:44Z"},{"alias_kind":"pith_short_12","alias_value":"K4MVO3GCR4CD","created_at":"2026-07-05T09:26:44Z"},{"alias_kind":"pith_short_16","alias_value":"K4MVO3GCR4CD3F2O","created_at":"2026-07-05T09:26:44Z"},{"alias_kind":"pith_short_8","alias_value":"K4MVO3GC","created_at":"2026-07-05T09:26:44Z"}],"graph_snapshots":[{"event_id":"sha256:39fe5cb32a0c7f75dff7722621d254232a5013758ada631b35cf5c263bdb099b","target":"graph","created_at":"2026-07-05T09:26:44Z","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/2410.20428/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large models are a hot research topic in the field of artificial intelligence. Leveraging their generative capabilities has the potential to enhance the level and quality of medical services. In response to the limitations of current large language models, which often struggle with accuracy and have narrow capabilities in medical applications, this paper presents a Chinese medical large language model, MedGo. MedGo was trained using a combination of high quality unsupervised medical data, supervised data, and preference alignment data, aimed at enhancing both its versatility and precision in m","authors_text":"Bo An, Haitao Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-27T12:52:52Z","title":"MedGo: A Chinese Medical Large Language Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.20428","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":"sha256:6863f47a696696a5724df5b615976542b3d541e4c4db4b79baf2696a5887ee4d","target":"record","created_at":"2026-07-05T09:26:44Z","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":"c961b12f7dae35fe18ecce1d3826fb40290e3e5073ee7b5b731aacdd0d43e85a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-27T12:52:52Z","title_canon_sha256":"6f75b3f64ea4012a5ba3bf0c77aa50f6eca4d7a0bc0bd70d4de11442ef10b0bc"},"schema_version":"1.0","source":{"id":"2410.20428","kind":"arxiv","version":1}},"canonical_sha256":"5719576cc28f043d974ea8c932227904a1db3f23987d4baa943cfd52890a0c3a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5719576cc28f043d974ea8c932227904a1db3f23987d4baa943cfd52890a0c3a","first_computed_at":"2026-07-05T09:26:44.750510Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:26:44.750510Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"h40n3GhyzD1A2fAqs9jTK1z1WPF7sckVfuAY9yOzt40eJS8BXGnXNBvRu4Muzi3eFnyXtyFuZoaOAk4f91EnBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:26:44.751012Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.20428","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6863f47a696696a5724df5b615976542b3d541e4c4db4b79baf2696a5887ee4d","sha256:39fe5cb32a0c7f75dff7722621d254232a5013758ada631b35cf5c263bdb099b"],"state_sha256":"a3225acfaa9f8af49e35dd51111c628112340d1e9141ef76f4a94972fbfe063e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ne3K57I8GxW+owOiyz7AJ3i7Zrf5bmjVOT4UMko7gQF6TVGB5Yk6iT0rHBrv/lPteUhXOLuVT+8LRKQodfFnCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T20:01:27.766880Z","bundle_sha256":"12e649aa7a6f1592d13c02da086f4284184513ed492da17b7384bae79c6fa302"}}