{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:JUJBATS4AZL2NWGQF4FWBT2IT4","short_pith_number":"pith:JUJBATS4","canonical_record":{"source":{"id":"2505.19110","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-25T11:55:02Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"560dcceb85cf259e7be2bc169d04b7186271ec55cd15e2aa665b28e64b920a63","abstract_canon_sha256":"efb1ebba5cfbc25a5c283aa9122cc56ee21e8c73ff9e29fb714088d90b2686b4"},"schema_version":"1.0"},"canonical_sha256":"4d12104e5c0657a6d8d02f0b60cf489f3e0cf3af6bd5f7839aca0f8eb862a23b","source":{"kind":"arxiv","id":"2505.19110","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.19110","created_at":"2026-07-05T11:13:26Z"},{"alias_kind":"arxiv_version","alias_value":"2505.19110v2","created_at":"2026-07-05T11:13:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.19110","created_at":"2026-07-05T11:13:26Z"},{"alias_kind":"pith_short_12","alias_value":"JUJBATS4AZL2","created_at":"2026-07-05T11:13:26Z"},{"alias_kind":"pith_short_16","alias_value":"JUJBATS4AZL2NWGQ","created_at":"2026-07-05T11:13:26Z"},{"alias_kind":"pith_short_8","alias_value":"JUJBATS4","created_at":"2026-07-05T11:13:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:JUJBATS4AZL2NWGQF4FWBT2IT4","target":"record","payload":{"canonical_record":{"source":{"id":"2505.19110","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-25T11:55:02Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"560dcceb85cf259e7be2bc169d04b7186271ec55cd15e2aa665b28e64b920a63","abstract_canon_sha256":"efb1ebba5cfbc25a5c283aa9122cc56ee21e8c73ff9e29fb714088d90b2686b4"},"schema_version":"1.0"},"canonical_sha256":"4d12104e5c0657a6d8d02f0b60cf489f3e0cf3af6bd5f7839aca0f8eb862a23b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:13:26.783225Z","signature_b64":"Y2CiqXXFKfehcnxosyYSIFBxg0JiWb0E7YsWNZRUNZteBXup8kb65wFnJim9zG0eZXCHTdjxaPM79UrsGW32Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4d12104e5c0657a6d8d02f0b60cf489f3e0cf3af6bd5f7839aca0f8eb862a23b","last_reissued_at":"2026-07-05T11:13:26.782779Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:13:26.782779Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.19110","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":"2026-07-05T11:13:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DP/YMVr5Wkj6LouqXYd26cBe3Fl2bBGUG+UMBRn3TfJ27G0k2tz0y43b8GCaS9xwVi8Xg3zKyOVNOtWyKxzFDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:53:50.798201Z"},"content_sha256":"5a86d420709a3e1b4c06ad4f1f1b0f815c7ac3c57f01050233281531dbe3928f","schema_version":"1.0","event_id":"sha256:5a86d420709a3e1b4c06ad4f1f1b0f815c7ac3c57f01050233281531dbe3928f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:JUJBATS4AZL2NWGQF4FWBT2IT4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Interpretable Representation Learning Approach for Diffusion Tensor Imaging","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Alberto Gaston Villagran Asiares, David R\\\"ugamer, Inga K\\\"orte, Kate Rendall, Luisa Sophie Schuhmacher, Simon Wei{\\ss}brod, Vishwa Mohan Singh","submitted_at":"2025-05-25T11:55:02Z","abstract_excerpt":"Diffusion Tensor Imaging (DTI) tractography offers detailed insights into the structural connectivity of the brain, but presents challenges in effective representation and interpretation in deep learning models. In this work, we propose a novel 2D representation of DTI tractography that encodes tract-level fractional anisotropy (FA) values into a 9x9 grayscale image. This representation is processed through a Beta-Total Correlation Variational Autoencoder with a Spatial Broadcast Decoder to learn a disentangled and interpretable latent embedding. We evaluate the quality of this embedding using"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.19110","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/2505.19110/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":"2026-07-05T11:13:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BnBMr+jkycW6FfoSsqpb5x9wrE9DxGgdmi/4cHVdLH4TDU+QvUURqVUlwO8oNqWFGe1gmwGNpykfK6wVKjhbDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:53:50.798741Z"},"content_sha256":"90acc1860fbf591615677540fa7ab5012276e0c4c7dc25bf4b440f9bc0f8c5fc","schema_version":"1.0","event_id":"sha256:90acc1860fbf591615677540fa7ab5012276e0c4c7dc25bf4b440f9bc0f8c5fc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JUJBATS4AZL2NWGQF4FWBT2IT4/bundle.json","state_url":"https://pith.science/pith/JUJBATS4AZL2NWGQF4FWBT2IT4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JUJBATS4AZL2NWGQF4FWBT2IT4/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":"2026-08-09T16:53:50Z","links":{"resolver":"https://pith.science/pith/JUJBATS4AZL2NWGQF4FWBT2IT4","bundle":"https://pith.science/pith/JUJBATS4AZL2NWGQF4FWBT2IT4/bundle.json","state":"https://pith.science/pith/JUJBATS4AZL2NWGQF4FWBT2IT4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JUJBATS4AZL2NWGQF4FWBT2IT4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:JUJBATS4AZL2NWGQF4FWBT2IT4","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":"efb1ebba5cfbc25a5c283aa9122cc56ee21e8c73ff9e29fb714088d90b2686b4","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-25T11:55:02Z","title_canon_sha256":"560dcceb85cf259e7be2bc169d04b7186271ec55cd15e2aa665b28e64b920a63"},"schema_version":"1.0","source":{"id":"2505.19110","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.19110","created_at":"2026-07-05T11:13:26Z"},{"alias_kind":"arxiv_version","alias_value":"2505.19110v2","created_at":"2026-07-05T11:13:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.19110","created_at":"2026-07-05T11:13:26Z"},{"alias_kind":"pith_short_12","alias_value":"JUJBATS4AZL2","created_at":"2026-07-05T11:13:26Z"},{"alias_kind":"pith_short_16","alias_value":"JUJBATS4AZL2NWGQ","created_at":"2026-07-05T11:13:26Z"},{"alias_kind":"pith_short_8","alias_value":"JUJBATS4","created_at":"2026-07-05T11:13:26Z"}],"graph_snapshots":[{"event_id":"sha256:90acc1860fbf591615677540fa7ab5012276e0c4c7dc25bf4b440f9bc0f8c5fc","target":"graph","created_at":"2026-07-05T11:13:26Z","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/2505.19110/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion Tensor Imaging (DTI) tractography offers detailed insights into the structural connectivity of the brain, but presents challenges in effective representation and interpretation in deep learning models. In this work, we propose a novel 2D representation of DTI tractography that encodes tract-level fractional anisotropy (FA) values into a 9x9 grayscale image. This representation is processed through a Beta-Total Correlation Variational Autoencoder with a Spatial Broadcast Decoder to learn a disentangled and interpretable latent embedding. We evaluate the quality of this embedding using","authors_text":"Alberto Gaston Villagran Asiares, David R\\\"ugamer, Inga K\\\"orte, Kate Rendall, Luisa Sophie Schuhmacher, Simon Wei{\\ss}brod, Vishwa Mohan Singh","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-25T11:55:02Z","title":"An Interpretable Representation Learning Approach for Diffusion Tensor Imaging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.19110","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":"sha256:5a86d420709a3e1b4c06ad4f1f1b0f815c7ac3c57f01050233281531dbe3928f","target":"record","created_at":"2026-07-05T11:13:26Z","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":"efb1ebba5cfbc25a5c283aa9122cc56ee21e8c73ff9e29fb714088d90b2686b4","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-25T11:55:02Z","title_canon_sha256":"560dcceb85cf259e7be2bc169d04b7186271ec55cd15e2aa665b28e64b920a63"},"schema_version":"1.0","source":{"id":"2505.19110","kind":"arxiv","version":2}},"canonical_sha256":"4d12104e5c0657a6d8d02f0b60cf489f3e0cf3af6bd5f7839aca0f8eb862a23b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4d12104e5c0657a6d8d02f0b60cf489f3e0cf3af6bd5f7839aca0f8eb862a23b","first_computed_at":"2026-07-05T11:13:26.782779Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:13:26.782779Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Y2CiqXXFKfehcnxosyYSIFBxg0JiWb0E7YsWNZRUNZteBXup8kb65wFnJim9zG0eZXCHTdjxaPM79UrsGW32Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:13:26.783225Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.19110","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5a86d420709a3e1b4c06ad4f1f1b0f815c7ac3c57f01050233281531dbe3928f","sha256:90acc1860fbf591615677540fa7ab5012276e0c4c7dc25bf4b440f9bc0f8c5fc"],"state_sha256":"fc40b233aeb2361e8fdfa26b2bebbe683669118bd9e8b316098b829aa30209cc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j/ffADpCag1BCBhKW/ni319kWHnzOruv3o9sy1ne96FIxIgNYxfgmmFRxrJLZ1UJKNNrKJ+QnkwVQaL+XbNGAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T16:53:50.805675Z","bundle_sha256":"fdf762130c587a3962dc7c0489ecc6a335f448b1451541ec3bde69fc545aa15c"}}