{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:SSEJFRFO2JGYJA3OF4A5P4CSRS","short_pith_number":"pith:SSEJFRFO","canonical_record":{"source":{"id":"2504.07246","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-04-09T19:35:31Z","cross_cats_sorted":[],"title_canon_sha256":"f857f6399ab77cece5f8793287f2c8123885cac4b5b09c294e2e8aff57e4bdbe","abstract_canon_sha256":"2fe6ff8cc8affb490a46fbf149e9064f7544da9354b7f5c0cd2d96d69f0163c6"},"schema_version":"1.0"},"canonical_sha256":"948892c4aed24d84836e2f01d7f0528cbcde51baf6aaafa503c5dac88f11351e","source":{"kind":"arxiv","id":"2504.07246","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.07246","created_at":"2026-07-05T10:49:53Z"},{"alias_kind":"arxiv_version","alias_value":"2504.07246v2","created_at":"2026-07-05T10:49:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.07246","created_at":"2026-07-05T10:49:53Z"},{"alias_kind":"pith_short_12","alias_value":"SSEJFRFO2JGY","created_at":"2026-07-05T10:49:53Z"},{"alias_kind":"pith_short_16","alias_value":"SSEJFRFO2JGYJA3O","created_at":"2026-07-05T10:49:53Z"},{"alias_kind":"pith_short_8","alias_value":"SSEJFRFO","created_at":"2026-07-05T10:49:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:SSEJFRFO2JGYJA3OF4A5P4CSRS","target":"record","payload":{"canonical_record":{"source":{"id":"2504.07246","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-04-09T19:35:31Z","cross_cats_sorted":[],"title_canon_sha256":"f857f6399ab77cece5f8793287f2c8123885cac4b5b09c294e2e8aff57e4bdbe","abstract_canon_sha256":"2fe6ff8cc8affb490a46fbf149e9064f7544da9354b7f5c0cd2d96d69f0163c6"},"schema_version":"1.0"},"canonical_sha256":"948892c4aed24d84836e2f01d7f0528cbcde51baf6aaafa503c5dac88f11351e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:49:53.182947Z","signature_b64":"Bxn/15IG1B+xHM2sxIGxcvS/P+Ni/npge0MDBB8DOw/CT8RiFuN/JTOKppRCqqXDZvMzJvtwM7zC5QMqpn/+BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"948892c4aed24d84836e2f01d7f0528cbcde51baf6aaafa503c5dac88f11351e","last_reissued_at":"2026-07-05T10:49:53.182396Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:49:53.182396Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.07246","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":"2026-07-05T10:49:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f2SQPs4il3HupVlr3vnOfVrgSXqZAaxo5/pTu/oHMqYMlEKj9QF/4gNCEaFaTuu/u/9j8FqcQUbCSKRRs8QjDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T02:02:12.251964Z"},"content_sha256":"e9edf51c1fbd85d9208dc8f7c099a0104cdf091aead24dde7718f74dcb1a249f","schema_version":"1.0","event_id":"sha256:e9edf51c1fbd85d9208dc8f7c099a0104cdf091aead24dde7718f74dcb1a249f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:SSEJFRFO2JGYJA3OF4A5P4CSRS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dual Deep Learning Approach for Non-invasive Renal Tumour Subtyping with VERDICT-MRI","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"David Atkinson, Eleftheria Panagiotaki, Joey Clemente, Lorna Smith, Lucy Caselton, Maxine Tran, Richard L Hesketh, Shonit Punwani, Snigdha Sen","submitted_at":"2025-04-09T19:35:31Z","abstract_excerpt":"This work aims to characterise renal tumour microstructure using diffusion MRI (dMRI); via the Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT)-MRI framework with self-supervised learning. Comprehensive datasets were acquired from 14 patients with 15 biopsy-confirmed renal tumours, with nine b-values in the range b=[0,2500]s/mm2. A three-compartment VERDICT model for renal tumours was fitted to the dMRI data using a self-supervised deep neural network, and ROIs were drawn by an experienced uroradiologist. An economical acquisition protocol for future studies "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.07246","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/2504.07246/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":"2026-07-05T10:49:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t6utwVsvnDmTtZgMhC7noqdJ5xd8lXRXZ63r9Y9SYNZWTWPeAITegwDCQjuRrybw6n0ybvajh7847walZN91DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T02:02:12.252715Z"},"content_sha256":"3e049505026e1a22a92a4176a25d0f5ff533f63c4295d2fed81826446f163786","schema_version":"1.0","event_id":"sha256:3e049505026e1a22a92a4176a25d0f5ff533f63c4295d2fed81826446f163786"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SSEJFRFO2JGYJA3OF4A5P4CSRS/bundle.json","state_url":"https://pith.science/pith/SSEJFRFO2JGYJA3OF4A5P4CSRS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SSEJFRFO2JGYJA3OF4A5P4CSRS/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":"2026-07-11T02:02:12Z","links":{"resolver":"https://pith.science/pith/SSEJFRFO2JGYJA3OF4A5P4CSRS","bundle":"https://pith.science/pith/SSEJFRFO2JGYJA3OF4A5P4CSRS/bundle.json","state":"https://pith.science/pith/SSEJFRFO2JGYJA3OF4A5P4CSRS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SSEJFRFO2JGYJA3OF4A5P4CSRS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SSEJFRFO2JGYJA3OF4A5P4CSRS","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":"2fe6ff8cc8affb490a46fbf149e9064f7544da9354b7f5c0cd2d96d69f0163c6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-04-09T19:35:31Z","title_canon_sha256":"f857f6399ab77cece5f8793287f2c8123885cac4b5b09c294e2e8aff57e4bdbe"},"schema_version":"1.0","source":{"id":"2504.07246","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.07246","created_at":"2026-07-05T10:49:53Z"},{"alias_kind":"arxiv_version","alias_value":"2504.07246v2","created_at":"2026-07-05T10:49:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.07246","created_at":"2026-07-05T10:49:53Z"},{"alias_kind":"pith_short_12","alias_value":"SSEJFRFO2JGY","created_at":"2026-07-05T10:49:53Z"},{"alias_kind":"pith_short_16","alias_value":"SSEJFRFO2JGYJA3O","created_at":"2026-07-05T10:49:53Z"},{"alias_kind":"pith_short_8","alias_value":"SSEJFRFO","created_at":"2026-07-05T10:49:53Z"}],"graph_snapshots":[{"event_id":"sha256:3e049505026e1a22a92a4176a25d0f5ff533f63c4295d2fed81826446f163786","target":"graph","created_at":"2026-07-05T10:49:53Z","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/2504.07246/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This work aims to characterise renal tumour microstructure using diffusion MRI (dMRI); via the Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT)-MRI framework with self-supervised learning. Comprehensive datasets were acquired from 14 patients with 15 biopsy-confirmed renal tumours, with nine b-values in the range b=[0,2500]s/mm2. A three-compartment VERDICT model for renal tumours was fitted to the dMRI data using a self-supervised deep neural network, and ROIs were drawn by an experienced uroradiologist. An economical acquisition protocol for future studies ","authors_text":"David Atkinson, Eleftheria Panagiotaki, Joey Clemente, Lorna Smith, Lucy Caselton, Maxine Tran, Richard L Hesketh, Shonit Punwani, Snigdha Sen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-04-09T19:35:31Z","title":"Dual Deep Learning Approach for Non-invasive Renal Tumour Subtyping with VERDICT-MRI"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.07246","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:e9edf51c1fbd85d9208dc8f7c099a0104cdf091aead24dde7718f74dcb1a249f","target":"record","created_at":"2026-07-05T10:49:53Z","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":"2fe6ff8cc8affb490a46fbf149e9064f7544da9354b7f5c0cd2d96d69f0163c6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-04-09T19:35:31Z","title_canon_sha256":"f857f6399ab77cece5f8793287f2c8123885cac4b5b09c294e2e8aff57e4bdbe"},"schema_version":"1.0","source":{"id":"2504.07246","kind":"arxiv","version":2}},"canonical_sha256":"948892c4aed24d84836e2f01d7f0528cbcde51baf6aaafa503c5dac88f11351e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"948892c4aed24d84836e2f01d7f0528cbcde51baf6aaafa503c5dac88f11351e","first_computed_at":"2026-07-05T10:49:53.182396Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:49:53.182396Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Bxn/15IG1B+xHM2sxIGxcvS/P+Ni/npge0MDBB8DOw/CT8RiFuN/JTOKppRCqqXDZvMzJvtwM7zC5QMqpn/+BA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:49:53.182947Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.07246","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e9edf51c1fbd85d9208dc8f7c099a0104cdf091aead24dde7718f74dcb1a249f","sha256:3e049505026e1a22a92a4176a25d0f5ff533f63c4295d2fed81826446f163786"],"state_sha256":"4c02d077b588003bd4f4c922e6f9254bedb43f95269c2e331837ede2645ec315"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+CYmKPmntSMQdQ1Pcm6mHjJqFOGogTzephfISRMXeofyCOB+Fin0Ksvq4XE/p/ekWbZihZyFEjW+Rm0ndky0BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-11T02:02:12.257113Z","bundle_sha256":"9eacfeaa0abbfd0886e6abff024780615bafba247e945cdff3fe19d0b5ebe803"}}