{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:CMB7IZAYMV7I3GXX4OVC2EWRGY","short_pith_number":"pith:CMB7IZAY","canonical_record":{"source":{"id":"2606.31171","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-30T06:01:54Z","cross_cats_sorted":["cs.ET"],"title_canon_sha256":"54433b518152ee40a0cf9e431ce8b22230331c062e35fa5e4ce2febb62a9b7b7","abstract_canon_sha256":"3967363113c289bf9d07de49fa9aea15a505a62d3a37516acdc4c6f6fa82bc27"},"schema_version":"1.0"},"canonical_sha256":"1303f46418657e8d9af7e3aa2d12d13604fe5cc7f6fa7dda61d20489280e57fb","source":{"kind":"arxiv","id":"2606.31171","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.31171","created_at":"2026-07-01T01:17:31Z"},{"alias_kind":"arxiv_version","alias_value":"2606.31171v1","created_at":"2026-07-01T01:17:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.31171","created_at":"2026-07-01T01:17:31Z"},{"alias_kind":"pith_short_12","alias_value":"CMB7IZAYMV7I","created_at":"2026-07-01T01:17:31Z"},{"alias_kind":"pith_short_16","alias_value":"CMB7IZAYMV7I3GXX","created_at":"2026-07-01T01:17:31Z"},{"alias_kind":"pith_short_8","alias_value":"CMB7IZAY","created_at":"2026-07-01T01:17:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:CMB7IZAYMV7I3GXX4OVC2EWRGY","target":"record","payload":{"canonical_record":{"source":{"id":"2606.31171","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-30T06:01:54Z","cross_cats_sorted":["cs.ET"],"title_canon_sha256":"54433b518152ee40a0cf9e431ce8b22230331c062e35fa5e4ce2febb62a9b7b7","abstract_canon_sha256":"3967363113c289bf9d07de49fa9aea15a505a62d3a37516acdc4c6f6fa82bc27"},"schema_version":"1.0"},"canonical_sha256":"1303f46418657e8d9af7e3aa2d12d13604fe5cc7f6fa7dda61d20489280e57fb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-01T01:17:31.108433Z","signature_b64":"P+283ME3/F7tUttBbrEVfZkUnacP6uHEVDPKS6ErUCRhIQeHgIxAOZ4oY6ueeD0qtNFsSFeUMwdN99pQzNCGBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1303f46418657e8d9af7e3aa2d12d13604fe5cc7f6fa7dda61d20489280e57fb","last_reissued_at":"2026-07-01T01:17:31.108023Z","signature_status":"signed_v1","first_computed_at":"2026-07-01T01:17:31.108023Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.31171","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":"2026-07-01T01:17:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PnQXPNljhJByUSKs7m1LMaeBcZLoLknkUtTqNDxLKbyEr45KORnm7ySp5gKUeBdUKAGgtypDZsYrhYKXo8sWDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-02T19:35:28.157792Z"},"content_sha256":"b477739ce14ccd0478ee2b510b4274d6731510525948734e9543f2594f03bbde","schema_version":"1.0","event_id":"sha256:b477739ce14ccd0478ee2b510b4274d6731510525948734e9543f2594f03bbde"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:CMB7IZAYMV7I3GXX4OVC2EWRGY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Cross-Domain Feature Expansion for Tabular Medical Data via Knowledge Graphs Injection","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.ET"],"primary_cat":"cs.AI","authors_text":"Guoping Liu, Haoyan Xin, Mengying Zhou, Yang Chen, Yongjie Yin","submitted_at":"2026-06-30T06:01:54Z","abstract_excerpt":"Acquiring comprehensive cross-domain biomedical profiles is often costly and time-consuming, resulting in severe data scarcity in medical research. To address this challenge, we propose MedKGTab, a knowledge-injected framework specifically engineered for cross-domain feature expansion in tabular medical data. MedKGTab seeks to infer uncollected biomedical features from available ones by exploiting their inherent statistical dependencies and established medical correlations. By employing a row-column dual-attention mechanism, MedKGTab operates directly on raw structured tabular data, inherently"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.31171","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/2606.31171/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":"2026-07-01T01:17:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kYHOmIvKD0YLd/MWeuHeheqF0cDkR4kGezwOIvIN6sT9RWBPh7ifDUKxWLknh+6nPfEzRUZtJ9DWG70ziXUkBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-02T19:35:28.158162Z"},"content_sha256":"c510eb66dca4c3a7fc688e9364cb810d8264434d60469f86be29256fbca5b3ce","schema_version":"1.0","event_id":"sha256:c510eb66dca4c3a7fc688e9364cb810d8264434d60469f86be29256fbca5b3ce"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CMB7IZAYMV7I3GXX4OVC2EWRGY/bundle.json","state_url":"https://pith.science/pith/CMB7IZAYMV7I3GXX4OVC2EWRGY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CMB7IZAYMV7I3GXX4OVC2EWRGY/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":"2026-07-02T19:35:28Z","links":{"resolver":"https://pith.science/pith/CMB7IZAYMV7I3GXX4OVC2EWRGY","bundle":"https://pith.science/pith/CMB7IZAYMV7I3GXX4OVC2EWRGY/bundle.json","state":"https://pith.science/pith/CMB7IZAYMV7I3GXX4OVC2EWRGY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CMB7IZAYMV7I3GXX4OVC2EWRGY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:CMB7IZAYMV7I3GXX4OVC2EWRGY","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":"3967363113c289bf9d07de49fa9aea15a505a62d3a37516acdc4c6f6fa82bc27","cross_cats_sorted":["cs.ET"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-30T06:01:54Z","title_canon_sha256":"54433b518152ee40a0cf9e431ce8b22230331c062e35fa5e4ce2febb62a9b7b7"},"schema_version":"1.0","source":{"id":"2606.31171","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.31171","created_at":"2026-07-01T01:17:31Z"},{"alias_kind":"arxiv_version","alias_value":"2606.31171v1","created_at":"2026-07-01T01:17:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.31171","created_at":"2026-07-01T01:17:31Z"},{"alias_kind":"pith_short_12","alias_value":"CMB7IZAYMV7I","created_at":"2026-07-01T01:17:31Z"},{"alias_kind":"pith_short_16","alias_value":"CMB7IZAYMV7I3GXX","created_at":"2026-07-01T01:17:31Z"},{"alias_kind":"pith_short_8","alias_value":"CMB7IZAY","created_at":"2026-07-01T01:17:31Z"}],"graph_snapshots":[{"event_id":"sha256:c510eb66dca4c3a7fc688e9364cb810d8264434d60469f86be29256fbca5b3ce","target":"graph","created_at":"2026-07-01T01:17:31Z","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/2606.31171/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Acquiring comprehensive cross-domain biomedical profiles is often costly and time-consuming, resulting in severe data scarcity in medical research. To address this challenge, we propose MedKGTab, a knowledge-injected framework specifically engineered for cross-domain feature expansion in tabular medical data. MedKGTab seeks to infer uncollected biomedical features from available ones by exploiting their inherent statistical dependencies and established medical correlations. By employing a row-column dual-attention mechanism, MedKGTab operates directly on raw structured tabular data, inherently","authors_text":"Guoping Liu, Haoyan Xin, Mengying Zhou, Yang Chen, Yongjie Yin","cross_cats":["cs.ET"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-30T06:01:54Z","title":"Cross-Domain Feature Expansion for Tabular Medical Data via Knowledge Graphs Injection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.31171","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:b477739ce14ccd0478ee2b510b4274d6731510525948734e9543f2594f03bbde","target":"record","created_at":"2026-07-01T01:17:31Z","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":"3967363113c289bf9d07de49fa9aea15a505a62d3a37516acdc4c6f6fa82bc27","cross_cats_sorted":["cs.ET"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-30T06:01:54Z","title_canon_sha256":"54433b518152ee40a0cf9e431ce8b22230331c062e35fa5e4ce2febb62a9b7b7"},"schema_version":"1.0","source":{"id":"2606.31171","kind":"arxiv","version":1}},"canonical_sha256":"1303f46418657e8d9af7e3aa2d12d13604fe5cc7f6fa7dda61d20489280e57fb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1303f46418657e8d9af7e3aa2d12d13604fe5cc7f6fa7dda61d20489280e57fb","first_computed_at":"2026-07-01T01:17:31.108023Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-01T01:17:31.108023Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"P+283ME3/F7tUttBbrEVfZkUnacP6uHEVDPKS6ErUCRhIQeHgIxAOZ4oY6ueeD0qtNFsSFeUMwdN99pQzNCGBQ==","signature_status":"signed_v1","signed_at":"2026-07-01T01:17:31.108433Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.31171","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b477739ce14ccd0478ee2b510b4274d6731510525948734e9543f2594f03bbde","sha256:c510eb66dca4c3a7fc688e9364cb810d8264434d60469f86be29256fbca5b3ce"],"state_sha256":"1ddd93b85a3107325fe5808e67dbbb22cdd0358e12b05f6b6ea239c7d3c86ec0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Tr9hzZdSGCWaThKNwmKPOlkPrTItSvE79zXhWkbBBWzov6r/wsogqU9qkoMMOoE2gJe+WxAiNCZYHDHSUO+bBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-02T19:35:28.160188Z","bundle_sha256":"08aafb667430df47af598d4e6c8f99ed700012feb804a28b0e281fdf72ca1aad"}}