{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:VSL6LLB2GTKKM5Y54C7RAKT26A","short_pith_number":"pith:VSL6LLB2","canonical_record":{"source":{"id":"2308.16376","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-08-31T00:36:10Z","cross_cats_sorted":["cs.CV","cs.DC"],"title_canon_sha256":"bab2dc16c3d5a392af2cc583f8a2fc0d136bf83fd472e896c9963f63c075cef6","abstract_canon_sha256":"bf5a690eb3d649fe1dc100ea2cd73cfcffb71f3b20922eab365c09b099f8a9b8"},"schema_version":"1.0"},"canonical_sha256":"ac97e5ac3a34d4a6771de0bf102a7af03ba96632ba487bca77bcf60c59ff7cac","source":{"kind":"arxiv","id":"2308.16376","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.16376","created_at":"2026-07-05T06:46:26Z"},{"alias_kind":"arxiv_version","alias_value":"2308.16376v1","created_at":"2026-07-05T06:46:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.16376","created_at":"2026-07-05T06:46:26Z"},{"alias_kind":"pith_short_12","alias_value":"VSL6LLB2GTKK","created_at":"2026-07-05T06:46:26Z"},{"alias_kind":"pith_short_16","alias_value":"VSL6LLB2GTKKM5Y5","created_at":"2026-07-05T06:46:26Z"},{"alias_kind":"pith_short_8","alias_value":"VSL6LLB2","created_at":"2026-07-05T06:46:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:VSL6LLB2GTKKM5Y54C7RAKT26A","target":"record","payload":{"canonical_record":{"source":{"id":"2308.16376","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-08-31T00:36:10Z","cross_cats_sorted":["cs.CV","cs.DC"],"title_canon_sha256":"bab2dc16c3d5a392af2cc583f8a2fc0d136bf83fd472e896c9963f63c075cef6","abstract_canon_sha256":"bf5a690eb3d649fe1dc100ea2cd73cfcffb71f3b20922eab365c09b099f8a9b8"},"schema_version":"1.0"},"canonical_sha256":"ac97e5ac3a34d4a6771de0bf102a7af03ba96632ba487bca77bcf60c59ff7cac","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:46:26.862350Z","signature_b64":"TrxKrZGdKAuRP8FUueHq1lkoqLpcRNDpI9PAvCjmiKfNWuPw8ie5n45aoKYa5FXRjKzRAmg8iVaezZiLYh+DAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ac97e5ac3a34d4a6771de0bf102a7af03ba96632ba487bca77bcf60c59ff7cac","last_reissued_at":"2026-07-05T06:46:26.861873Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:46:26.861873Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.16376","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":"2026-07-05T06:46:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C07EPUIZa+WEOxDXPWmBv7/i23F2kvhP64cvkaoi/kOHGm8koLtfsoOf+5X1EbRT89bjgRbcBOEKYrDyDXddBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:11:20.480257Z"},"content_sha256":"945f6cb09443a4d6684fc51efb5732366a0eb47665500a34bbfd59769ef05cdf","schema_version":"1.0","event_id":"sha256:945f6cb09443a4d6684fc51efb5732366a0eb47665500a34bbfd59769ef05cdf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:VSL6LLB2GTKKM5Y54C7RAKT26A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving Multiple Sclerosis Lesion Segmentation Across Clinical Sites: A Federated Learning Approach with Noise-Resilient Training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.DC"],"primary_cat":"eess.IV","authors_text":"Aria Nguyen, Chenyu Wang, Chun-Chien Shieh, Dongang Wang, Dongnan Liu, Fernando Calamante, Geng Zhan, Hengrui Wang, Kain Kyle, Lei Bai, Linda Ly, Mariano Cabezas, Michael Barnett, Ryan Sullivan, Wanli Ouyang, Weidong Cai","submitted_at":"2023-08-31T00:36:10Z","abstract_excerpt":"Accurately measuring the evolution of Multiple Sclerosis (MS) with magnetic resonance imaging (MRI) critically informs understanding of disease progression and helps to direct therapeutic strategy. Deep learning models have shown promise for automatically segmenting MS lesions, but the scarcity of accurately annotated data hinders progress in this area. Obtaining sufficient data from a single clinical site is challenging and does not address the heterogeneous need for model robustness. Conversely, the collection of data from multiple sites introduces data privacy concerns and potential label n"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.16376","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/2308.16376/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":"2026-07-05T06:46:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b3Aag5jS3Rbr+a38Aaf3seho+6yiMJqYJsgWwmhLYm4byFtZZOsyMP3irYWIYdWQ7UF4m4TiHKqu0lrHaNWECQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:11:20.480645Z"},"content_sha256":"5c2b870facc7e3b99be36fad557664dcba1cb7cbd0e7fe4d9bcd07659b25c785","schema_version":"1.0","event_id":"sha256:5c2b870facc7e3b99be36fad557664dcba1cb7cbd0e7fe4d9bcd07659b25c785"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VSL6LLB2GTKKM5Y54C7RAKT26A/bundle.json","state_url":"https://pith.science/pith/VSL6LLB2GTKKM5Y54C7RAKT26A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VSL6LLB2GTKKM5Y54C7RAKT26A/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":"2026-07-07T04:11:20Z","links":{"resolver":"https://pith.science/pith/VSL6LLB2GTKKM5Y54C7RAKT26A","bundle":"https://pith.science/pith/VSL6LLB2GTKKM5Y54C7RAKT26A/bundle.json","state":"https://pith.science/pith/VSL6LLB2GTKKM5Y54C7RAKT26A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VSL6LLB2GTKKM5Y54C7RAKT26A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:VSL6LLB2GTKKM5Y54C7RAKT26A","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":"bf5a690eb3d649fe1dc100ea2cd73cfcffb71f3b20922eab365c09b099f8a9b8","cross_cats_sorted":["cs.CV","cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-08-31T00:36:10Z","title_canon_sha256":"bab2dc16c3d5a392af2cc583f8a2fc0d136bf83fd472e896c9963f63c075cef6"},"schema_version":"1.0","source":{"id":"2308.16376","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.16376","created_at":"2026-07-05T06:46:26Z"},{"alias_kind":"arxiv_version","alias_value":"2308.16376v1","created_at":"2026-07-05T06:46:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.16376","created_at":"2026-07-05T06:46:26Z"},{"alias_kind":"pith_short_12","alias_value":"VSL6LLB2GTKK","created_at":"2026-07-05T06:46:26Z"},{"alias_kind":"pith_short_16","alias_value":"VSL6LLB2GTKKM5Y5","created_at":"2026-07-05T06:46:26Z"},{"alias_kind":"pith_short_8","alias_value":"VSL6LLB2","created_at":"2026-07-05T06:46:26Z"}],"graph_snapshots":[{"event_id":"sha256:5c2b870facc7e3b99be36fad557664dcba1cb7cbd0e7fe4d9bcd07659b25c785","target":"graph","created_at":"2026-07-05T06:46:26Z","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/2308.16376/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurately measuring the evolution of Multiple Sclerosis (MS) with magnetic resonance imaging (MRI) critically informs understanding of disease progression and helps to direct therapeutic strategy. Deep learning models have shown promise for automatically segmenting MS lesions, but the scarcity of accurately annotated data hinders progress in this area. Obtaining sufficient data from a single clinical site is challenging and does not address the heterogeneous need for model robustness. Conversely, the collection of data from multiple sites introduces data privacy concerns and potential label n","authors_text":"Aria Nguyen, Chenyu Wang, Chun-Chien Shieh, Dongang Wang, Dongnan Liu, Fernando Calamante, Geng Zhan, Hengrui Wang, Kain Kyle, Lei Bai, Linda Ly, Mariano Cabezas, Michael Barnett, Ryan Sullivan, Wanli Ouyang, Weidong Cai","cross_cats":["cs.CV","cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-08-31T00:36:10Z","title":"Improving Multiple Sclerosis Lesion Segmentation Across Clinical Sites: A Federated Learning Approach with Noise-Resilient Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.16376","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":"sha256:945f6cb09443a4d6684fc51efb5732366a0eb47665500a34bbfd59769ef05cdf","target":"record","created_at":"2026-07-05T06:46:26Z","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":"bf5a690eb3d649fe1dc100ea2cd73cfcffb71f3b20922eab365c09b099f8a9b8","cross_cats_sorted":["cs.CV","cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-08-31T00:36:10Z","title_canon_sha256":"bab2dc16c3d5a392af2cc583f8a2fc0d136bf83fd472e896c9963f63c075cef6"},"schema_version":"1.0","source":{"id":"2308.16376","kind":"arxiv","version":1}},"canonical_sha256":"ac97e5ac3a34d4a6771de0bf102a7af03ba96632ba487bca77bcf60c59ff7cac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ac97e5ac3a34d4a6771de0bf102a7af03ba96632ba487bca77bcf60c59ff7cac","first_computed_at":"2026-07-05T06:46:26.861873Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:46:26.861873Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TrxKrZGdKAuRP8FUueHq1lkoqLpcRNDpI9PAvCjmiKfNWuPw8ie5n45aoKYa5FXRjKzRAmg8iVaezZiLYh+DAg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:46:26.862350Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.16376","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:945f6cb09443a4d6684fc51efb5732366a0eb47665500a34bbfd59769ef05cdf","sha256:5c2b870facc7e3b99be36fad557664dcba1cb7cbd0e7fe4d9bcd07659b25c785"],"state_sha256":"e5a141635f3ce0dc96d2bb56daf8d6626855c963b7356570566b0c62ba8617ff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DOPAMvfh7ImcowutI/C23RbfuUwMehbX8YAl8AmINUxZU/UwKo1na0PcQgjET7Q3Vi1jUUybcyijYumJ3OKMCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T04:11:20.482707Z","bundle_sha256":"0a4bda186b98e099fc9c5fbe20e2c700efece9592818882baf446ae6e7064bd7"}}