{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:TFGJQJ6BSNJSTWIIJSKZR44BOM","short_pith_number":"pith:TFGJQJ6B","canonical_record":{"source":{"id":"2606.04414","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-03T03:45:11Z","cross_cats_sorted":["cs.MM"],"title_canon_sha256":"ef004795b946d5ee7d2d59d1b46b0c85858748578c7d889aea1cc1fbe03c1d83","abstract_canon_sha256":"7595b5651ced6f2bed27a6d8e28c899320e4798c7d949f36f7df539ed68fd728"},"schema_version":"1.0"},"canonical_sha256":"994c9827c1935329d9084c9598f381733e5f20e4a3926492c8fa1bb7b9f44f3e","source":{"kind":"arxiv","id":"2606.04414","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.04414","created_at":"2026-06-04T01:09:07Z"},{"alias_kind":"arxiv_version","alias_value":"2606.04414v1","created_at":"2026-06-04T01:09:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.04414","created_at":"2026-06-04T01:09:07Z"},{"alias_kind":"pith_short_12","alias_value":"TFGJQJ6BSNJS","created_at":"2026-06-04T01:09:07Z"},{"alias_kind":"pith_short_16","alias_value":"TFGJQJ6BSNJSTWII","created_at":"2026-06-04T01:09:07Z"},{"alias_kind":"pith_short_8","alias_value":"TFGJQJ6B","created_at":"2026-06-04T01:09:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:TFGJQJ6BSNJSTWIIJSKZR44BOM","target":"record","payload":{"canonical_record":{"source":{"id":"2606.04414","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-03T03:45:11Z","cross_cats_sorted":["cs.MM"],"title_canon_sha256":"ef004795b946d5ee7d2d59d1b46b0c85858748578c7d889aea1cc1fbe03c1d83","abstract_canon_sha256":"7595b5651ced6f2bed27a6d8e28c899320e4798c7d949f36f7df539ed68fd728"},"schema_version":"1.0"},"canonical_sha256":"994c9827c1935329d9084c9598f381733e5f20e4a3926492c8fa1bb7b9f44f3e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-04T01:09:07.134039Z","signature_b64":"Bxcl4PYVSKCMI4ctJNULQxjxDtuiW7vldBdE63JTFD8FMKGjPY0FAL8Dw6JkLocFz7c2ybanAvABGSvmg38mAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"994c9827c1935329d9084c9598f381733e5f20e4a3926492c8fa1bb7b9f44f3e","last_reissued_at":"2026-06-04T01:09:07.133372Z","signature_status":"signed_v1","first_computed_at":"2026-06-04T01:09:07.133372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.04414","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":"2026-06-04T01:09:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pQF6SEt7MVUeFRx2VJm/9h9FA58Fq4tdD77lGUQ+U/z83s0oQ6ug5pHABLkHinZKF/myhqykq2kG3Q1LuKzICg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T07:45:05.914852Z"},"content_sha256":"fb7dd2e83d86bcb1118b6151b083c2e81a689b57cd02b715c4da0cbeca786e77","schema_version":"1.0","event_id":"sha256:fb7dd2e83d86bcb1118b6151b083c2e81a689b57cd02b715c4da0cbeca786e77"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:TFGJQJ6BSNJSTWIIJSKZR44BOM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Motion-Guided Causal Disentanglement for Robust Multi-View Cine Cardiac MRI Diagnosis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"cs.CV","authors_text":"Amit Patel, Chuankai Xu, Cristiane De Carvalho Singulane, Diego Perez de Arenaza, Fabio Fernandes, Jane Cao, Jeremy Slivnick, Jianxin Xie, Karolina Zareba, Mohammad Abuannadi, Seth Uretsky, Stephen Chandler, Vidya Nadig","submitted_at":"2026-06-03T03:45:11Z","abstract_excerpt":"Multi-view cardiac magnetic resonance (CMR) imaging provides complementary anatomical information and is widely used for noninvasive disease assessment. Recent transformer-based models have demonstrated strong representation learning capabilities for CMR analysis; however, they typically learn unified latent embeddings that entangle view-specific anatomical variations with disease-related features. Such entanglement biases classifiers toward structural attributes rather than view-invariant pathological patterns. This issue is exacerbated in low-data regimes, particularly for underrepresented c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.04414","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/2606.04414/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":"2026-06-04T01:09:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z2Xa/dPlL8azhVn5eP+JRKE1AsUxoCYk7pZO5JQXxZP7BrArzN7sVvAWV+eK9VZoYbGADaHrEXlkHxZ05CeVBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T07:45:05.915572Z"},"content_sha256":"910a9a01d6424d54d5aceaee1a89f0efb01cb7375a06e95ecbc3d8452fce77d9","schema_version":"1.0","event_id":"sha256:910a9a01d6424d54d5aceaee1a89f0efb01cb7375a06e95ecbc3d8452fce77d9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TFGJQJ6BSNJSTWIIJSKZR44BOM/bundle.json","state_url":"https://pith.science/pith/TFGJQJ6BSNJSTWIIJSKZR44BOM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TFGJQJ6BSNJSTWIIJSKZR44BOM/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":"2026-06-09T07:45:05Z","links":{"resolver":"https://pith.science/pith/TFGJQJ6BSNJSTWIIJSKZR44BOM","bundle":"https://pith.science/pith/TFGJQJ6BSNJSTWIIJSKZR44BOM/bundle.json","state":"https://pith.science/pith/TFGJQJ6BSNJSTWIIJSKZR44BOM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TFGJQJ6BSNJSTWIIJSKZR44BOM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:TFGJQJ6BSNJSTWIIJSKZR44BOM","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":"7595b5651ced6f2bed27a6d8e28c899320e4798c7d949f36f7df539ed68fd728","cross_cats_sorted":["cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-03T03:45:11Z","title_canon_sha256":"ef004795b946d5ee7d2d59d1b46b0c85858748578c7d889aea1cc1fbe03c1d83"},"schema_version":"1.0","source":{"id":"2606.04414","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.04414","created_at":"2026-06-04T01:09:07Z"},{"alias_kind":"arxiv_version","alias_value":"2606.04414v1","created_at":"2026-06-04T01:09:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.04414","created_at":"2026-06-04T01:09:07Z"},{"alias_kind":"pith_short_12","alias_value":"TFGJQJ6BSNJS","created_at":"2026-06-04T01:09:07Z"},{"alias_kind":"pith_short_16","alias_value":"TFGJQJ6BSNJSTWII","created_at":"2026-06-04T01:09:07Z"},{"alias_kind":"pith_short_8","alias_value":"TFGJQJ6B","created_at":"2026-06-04T01:09:07Z"}],"graph_snapshots":[{"event_id":"sha256:910a9a01d6424d54d5aceaee1a89f0efb01cb7375a06e95ecbc3d8452fce77d9","target":"graph","created_at":"2026-06-04T01:09:07Z","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/2606.04414/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-view cardiac magnetic resonance (CMR) imaging provides complementary anatomical information and is widely used for noninvasive disease assessment. Recent transformer-based models have demonstrated strong representation learning capabilities for CMR analysis; however, they typically learn unified latent embeddings that entangle view-specific anatomical variations with disease-related features. Such entanglement biases classifiers toward structural attributes rather than view-invariant pathological patterns. This issue is exacerbated in low-data regimes, particularly for underrepresented c","authors_text":"Amit Patel, Chuankai Xu, Cristiane De Carvalho Singulane, Diego Perez de Arenaza, Fabio Fernandes, Jane Cao, Jeremy Slivnick, Jianxin Xie, Karolina Zareba, Mohammad Abuannadi, Seth Uretsky, Stephen Chandler, Vidya Nadig","cross_cats":["cs.MM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-03T03:45:11Z","title":"Motion-Guided Causal Disentanglement for Robust Multi-View Cine Cardiac MRI Diagnosis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.04414","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:fb7dd2e83d86bcb1118b6151b083c2e81a689b57cd02b715c4da0cbeca786e77","target":"record","created_at":"2026-06-04T01:09:07Z","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":"7595b5651ced6f2bed27a6d8e28c899320e4798c7d949f36f7df539ed68fd728","cross_cats_sorted":["cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-03T03:45:11Z","title_canon_sha256":"ef004795b946d5ee7d2d59d1b46b0c85858748578c7d889aea1cc1fbe03c1d83"},"schema_version":"1.0","source":{"id":"2606.04414","kind":"arxiv","version":1}},"canonical_sha256":"994c9827c1935329d9084c9598f381733e5f20e4a3926492c8fa1bb7b9f44f3e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"994c9827c1935329d9084c9598f381733e5f20e4a3926492c8fa1bb7b9f44f3e","first_computed_at":"2026-06-04T01:09:07.133372Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-04T01:09:07.133372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Bxcl4PYVSKCMI4ctJNULQxjxDtuiW7vldBdE63JTFD8FMKGjPY0FAL8Dw6JkLocFz7c2ybanAvABGSvmg38mAw==","signature_status":"signed_v1","signed_at":"2026-06-04T01:09:07.134039Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.04414","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fb7dd2e83d86bcb1118b6151b083c2e81a689b57cd02b715c4da0cbeca786e77","sha256:910a9a01d6424d54d5aceaee1a89f0efb01cb7375a06e95ecbc3d8452fce77d9"],"state_sha256":"273313a6bee2378f32150ba186f1f1cc18db0120003669be34a165457b2452bb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iZEneEuF6agAU+FVdv2VUwlGDNzU80pt5IVd6GA2OPi9SjIrWXLLmX0hqGUvuLQv8zAJsdtvjKcViwYl0nS5BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T07:45:05.919547Z","bundle_sha256":"ec6d27ee63ad2798cdffb58cf14618f6aec420f69e449aa58fcc82869aff7d0c"}}