{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:6PHY4BPVBMNOC3LKXFK4I4Z464","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":"7801e86575aff6b1c2d85e8548eef2569de71ec20ad6b6e4bdca99735c997f63","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-02-12T01:03:39Z","title_canon_sha256":"a8b3664699de6d122814f99cfe889bd33cca105f682fe81a1646c53aa830b8d0"},"schema_version":"1.0","source":{"id":"2402.07354","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.07354","created_at":"2026-07-05T08:06:27Z"},{"alias_kind":"arxiv_version","alias_value":"2402.07354v4","created_at":"2026-07-05T08:06:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.07354","created_at":"2026-07-05T08:06:27Z"},{"alias_kind":"pith_short_12","alias_value":"6PHY4BPVBMNO","created_at":"2026-07-05T08:06:27Z"},{"alias_kind":"pith_short_16","alias_value":"6PHY4BPVBMNOC3LK","created_at":"2026-07-05T08:06:27Z"},{"alias_kind":"pith_short_8","alias_value":"6PHY4BPV","created_at":"2026-07-05T08:06:27Z"}],"graph_snapshots":[{"event_id":"sha256:367e213f24a245ed6bf677b829503055c5a5ba26c9a508510144d4c7f6b5e23a","target":"graph","created_at":"2026-07-05T08:06:27Z","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/2402.07354/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Identification of tumor margins is essential for surgical decision-making for glioblastoma patients and provides reliable assistance for neurosurgeons. Despite improvements in deep learning architectures for tumor segmentation over the years, creating a fully autonomous system suitable for clinical floors remains a formidable challenge because the model predictions have not yet reached the desired level of accuracy and generalizability for clinical applications. Generative modeling techniques have seen significant improvements in recent times. Specifically, Generative Adversarial Networks (GAN","authors_text":"Abhishek Sharma, Agamdeep Chopra, Ethan Honey, Harshitha Rebala, Jacob Ruzevick, Juampablo Heras Rivera, Mehmet Kurt, Tianyi Ren","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-02-12T01:03:39Z","title":"Re-DiffiNet: Modeling discrepancies in tumor segmentation using diffusion models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.07354","kind":"arxiv","version":4},"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":"sha256:1ebcc5465d4c223206856998fe456983fa792c4b0ac591b06da75f959b48c05e","target":"record","created_at":"2026-07-05T08:06:27Z","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":"7801e86575aff6b1c2d85e8548eef2569de71ec20ad6b6e4bdca99735c997f63","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-02-12T01:03:39Z","title_canon_sha256":"a8b3664699de6d122814f99cfe889bd33cca105f682fe81a1646c53aa830b8d0"},"schema_version":"1.0","source":{"id":"2402.07354","kind":"arxiv","version":4}},"canonical_sha256":"f3cf8e05f50b1ae16d6ab955c4733cf7325db0a278597cf20e63820bf0ee040c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f3cf8e05f50b1ae16d6ab955c4733cf7325db0a278597cf20e63820bf0ee040c","first_computed_at":"2026-07-05T08:06:27.787233Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:06:27.787233Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ua3jfnvdzEnK3cNHSc8cEK2HhCsUZ5gur5HVjoS9BIdnMTZIDZqOylRN4Ygk9EBikQ5xYaaJtRrc7IaAdJrPBw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:06:27.787699Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.07354","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1ebcc5465d4c223206856998fe456983fa792c4b0ac591b06da75f959b48c05e","sha256:367e213f24a245ed6bf677b829503055c5a5ba26c9a508510144d4c7f6b5e23a"],"state_sha256":"00d781ec2f47af5f5518a0f533029749e9e0b928e60d7df90f73ef7d677cf098"}