{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:D45U5DZP7E5BRWFWWQTKJSTLIE","short_pith_number":"pith:D45U5DZP","canonical_record":{"source":{"id":"2404.12278","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-04-18T15:52:42Z","cross_cats_sorted":[],"title_canon_sha256":"d6e9727e29e77d4891e873e014a0a93c8fc0ea39a960f37e005860b57a3171c2","abstract_canon_sha256":"981f1b9b869d5a9d76b62f9233e9fbeab1b48f18658cec89b6fb35877af7ffa8"},"schema_version":"1.0"},"canonical_sha256":"1f3b4e8f2ff93a18d8b6b426a4ca6b411cb156bc3ea8d98e94298b14c484b2af","source":{"kind":"arxiv","id":"2404.12278","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.12278","created_at":"2026-07-05T08:26:23Z"},{"alias_kind":"arxiv_version","alias_value":"2404.12278v2","created_at":"2026-07-05T08:26:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.12278","created_at":"2026-07-05T08:26:23Z"},{"alias_kind":"pith_short_12","alias_value":"D45U5DZP7E5B","created_at":"2026-07-05T08:26:23Z"},{"alias_kind":"pith_short_16","alias_value":"D45U5DZP7E5BRWFW","created_at":"2026-07-05T08:26:23Z"},{"alias_kind":"pith_short_8","alias_value":"D45U5DZP","created_at":"2026-07-05T08:26:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:D45U5DZP7E5BRWFWWQTKJSTLIE","target":"record","payload":{"canonical_record":{"source":{"id":"2404.12278","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-04-18T15:52:42Z","cross_cats_sorted":[],"title_canon_sha256":"d6e9727e29e77d4891e873e014a0a93c8fc0ea39a960f37e005860b57a3171c2","abstract_canon_sha256":"981f1b9b869d5a9d76b62f9233e9fbeab1b48f18658cec89b6fb35877af7ffa8"},"schema_version":"1.0"},"canonical_sha256":"1f3b4e8f2ff93a18d8b6b426a4ca6b411cb156bc3ea8d98e94298b14c484b2af","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:26:23.067898Z","signature_b64":"inqcGaPlt8qUHRUp7TfOL1anE3/e1wjbxdPCVJczCpbg5imEPeIhEmHCPb+H5Z7MAQe6SeihAwZ4KHLviNntAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1f3b4e8f2ff93a18d8b6b426a4ca6b411cb156bc3ea8d98e94298b14c484b2af","last_reissued_at":"2026-07-05T08:26:23.067479Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:26:23.067479Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.12278","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:26:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LIzPrSYXVf0+B2lfz+6JAG2C33n3Lw/3ViXXhmHskQzsCjBYxnYpUHQjbbuDlXx/JKmgXbRKbIwLgrg0odfiBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T18:33:56.709318Z"},"content_sha256":"b10a5f61e8fc18d8c96802695abb24c75b0cddac34796bd41843ae52cf48033a","schema_version":"1.0","event_id":"sha256:b10a5f61e8fc18d8c96802695abb24c75b0cddac34796bd41843ae52cf48033a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:D45U5DZP7E5BRWFWWQTKJSTLIE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DF-DM: A foundational process model for multimodal data fusion in the artificial intelligence era","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Chenwei Wu, Constanza V\\'asquez-Venegas, David Restrepo, Diego M L\\'opez, Leo Anthony Celi, Luis Filipe Nakayama","submitted_at":"2024-04-18T15:52:42Z","abstract_excerpt":"In the big data era, integrating diverse data modalities poses significant challenges, particularly in complex fields like healthcare. This paper introduces a new process model for multimodal Data Fusion for Data Mining, integrating embeddings and the Cross-Industry Standard Process for Data Mining with the existing Data Fusion Information Group model. Our model aims to decrease computational costs, complexity, and bias while improving efficiency and reliability. We also propose \"disentangled dense fusion\", a novel embedding fusion method designed to optimize mutual information and facilitate "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.12278","kind":"arxiv","version":2},"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/2404.12278/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":"2026-07-05T08:26:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jcZktJM/oKgBzvARRhPR+uU97VAOxyWLloWQPNnVqwnjkeSTmg3XAP2sGYbozDaMwjgopZNXuYYjabWGBlIYCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T18:33:56.709833Z"},"content_sha256":"2aac3edc789e4a1ebc1e8f91b7eadaf0effa75454f1967277fd6f18f78443ec4","schema_version":"1.0","event_id":"sha256:2aac3edc789e4a1ebc1e8f91b7eadaf0effa75454f1967277fd6f18f78443ec4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D45U5DZP7E5BRWFWWQTKJSTLIE/bundle.json","state_url":"https://pith.science/pith/D45U5DZP7E5BRWFWWQTKJSTLIE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D45U5DZP7E5BRWFWWQTKJSTLIE/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":"2026-08-07T18:33:56Z","links":{"resolver":"https://pith.science/pith/D45U5DZP7E5BRWFWWQTKJSTLIE","bundle":"https://pith.science/pith/D45U5DZP7E5BRWFWWQTKJSTLIE/bundle.json","state":"https://pith.science/pith/D45U5DZP7E5BRWFWWQTKJSTLIE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D45U5DZP7E5BRWFWWQTKJSTLIE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:D45U5DZP7E5BRWFWWQTKJSTLIE","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":"981f1b9b869d5a9d76b62f9233e9fbeab1b48f18658cec89b6fb35877af7ffa8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-04-18T15:52:42Z","title_canon_sha256":"d6e9727e29e77d4891e873e014a0a93c8fc0ea39a960f37e005860b57a3171c2"},"schema_version":"1.0","source":{"id":"2404.12278","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.12278","created_at":"2026-07-05T08:26:23Z"},{"alias_kind":"arxiv_version","alias_value":"2404.12278v2","created_at":"2026-07-05T08:26:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.12278","created_at":"2026-07-05T08:26:23Z"},{"alias_kind":"pith_short_12","alias_value":"D45U5DZP7E5B","created_at":"2026-07-05T08:26:23Z"},{"alias_kind":"pith_short_16","alias_value":"D45U5DZP7E5BRWFW","created_at":"2026-07-05T08:26:23Z"},{"alias_kind":"pith_short_8","alias_value":"D45U5DZP","created_at":"2026-07-05T08:26:23Z"}],"graph_snapshots":[{"event_id":"sha256:2aac3edc789e4a1ebc1e8f91b7eadaf0effa75454f1967277fd6f18f78443ec4","target":"graph","created_at":"2026-07-05T08:26:23Z","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/2404.12278/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In the big data era, integrating diverse data modalities poses significant challenges, particularly in complex fields like healthcare. This paper introduces a new process model for multimodal Data Fusion for Data Mining, integrating embeddings and the Cross-Industry Standard Process for Data Mining with the existing Data Fusion Information Group model. Our model aims to decrease computational costs, complexity, and bias while improving efficiency and reliability. We also propose \"disentangled dense fusion\", a novel embedding fusion method designed to optimize mutual information and facilitate ","authors_text":"Chenwei Wu, Constanza V\\'asquez-Venegas, David Restrepo, Diego M L\\'opez, Leo Anthony Celi, Luis Filipe Nakayama","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-04-18T15:52:42Z","title":"DF-DM: A foundational process model for multimodal data fusion in the artificial intelligence era"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.12278","kind":"arxiv","version":2},"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:b10a5f61e8fc18d8c96802695abb24c75b0cddac34796bd41843ae52cf48033a","target":"record","created_at":"2026-07-05T08:26:23Z","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":"981f1b9b869d5a9d76b62f9233e9fbeab1b48f18658cec89b6fb35877af7ffa8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-04-18T15:52:42Z","title_canon_sha256":"d6e9727e29e77d4891e873e014a0a93c8fc0ea39a960f37e005860b57a3171c2"},"schema_version":"1.0","source":{"id":"2404.12278","kind":"arxiv","version":2}},"canonical_sha256":"1f3b4e8f2ff93a18d8b6b426a4ca6b411cb156bc3ea8d98e94298b14c484b2af","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1f3b4e8f2ff93a18d8b6b426a4ca6b411cb156bc3ea8d98e94298b14c484b2af","first_computed_at":"2026-07-05T08:26:23.067479Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:26:23.067479Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"inqcGaPlt8qUHRUp7TfOL1anE3/e1wjbxdPCVJczCpbg5imEPeIhEmHCPb+H5Z7MAQe6SeihAwZ4KHLviNntAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:26:23.067898Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.12278","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b10a5f61e8fc18d8c96802695abb24c75b0cddac34796bd41843ae52cf48033a","sha256:2aac3edc789e4a1ebc1e8f91b7eadaf0effa75454f1967277fd6f18f78443ec4"],"state_sha256":"bfb96a1a4934575bf3c9c7bc3cb2e48266bd3d77970c65a9c6034dd89b833af7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"It2xGPSdWjP/k3LYCYYQdvH/8d6bL+KmlIHRfuhkvbQW62/Gqs4mYXkKA+zVOxnbY4D+efcpLC7hSo9luQsNCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T18:33:56.715170Z","bundle_sha256":"a8737937fbcac0743c37e86ac242bb5a1f127cf718b24c3a23a225cf7e3d43b7"}}