{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:LKDNDGWB4BQX5ENHZGAYSXFICJ","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":"179bea9385e7557f97466c62cde553292ed4a07025ed20941a766671a9912c4f","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2023-02-07T13:58:08Z","title_canon_sha256":"bb2bb12ae7941bbd69b225105be1858bf6e8465676f4b2503a11ffdbb8735440"},"schema_version":"1.0","source":{"id":"2302.03473","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.03473","created_at":"2026-07-05T05:39:37Z"},{"alias_kind":"arxiv_version","alias_value":"2302.03473v1","created_at":"2026-07-05T05:39:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.03473","created_at":"2026-07-05T05:39:37Z"},{"alias_kind":"pith_short_12","alias_value":"LKDNDGWB4BQX","created_at":"2026-07-05T05:39:37Z"},{"alias_kind":"pith_short_16","alias_value":"LKDNDGWB4BQX5ENH","created_at":"2026-07-05T05:39:37Z"},{"alias_kind":"pith_short_8","alias_value":"LKDNDGWB","created_at":"2026-07-05T05:39:37Z"}],"graph_snapshots":[{"event_id":"sha256:e45e3ea83a0ce134b33859ed3594d7ef5002275bab81f26b7ab8fd7506d1d167","target":"graph","created_at":"2026-07-05T05:39:37Z","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/2302.03473/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Access to the proper infrastructure is critical when performing medical image segmentation with Deep Learning. This requirement makes it difficult to run state-of-the-art segmentation models in resource-constrained scenarios like primary care facilities in rural areas and during crises. The recently emerging field of Neural Cellular Automata (NCA) has shown that locally interacting one-cell models can achieve competitive results in tasks such as image generation or segmentations in low-resolution inputs. However, they are constrained by high VRAM requirements and the difficulty of reaching con","authors_text":"Anirban Mukhopadhyay, Camila Gonz\\'alez, John Kalkhof","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2023-02-07T13:58:08Z","title":"Med-NCA: Robust and Lightweight Segmentation with Neural Cellular Automata"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.03473","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":"sha256:0dd9fc934f81fee3063d1fceced959f24e845dddac33c606b800b19626d75bcb","target":"record","created_at":"2026-07-05T05:39:37Z","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":"179bea9385e7557f97466c62cde553292ed4a07025ed20941a766671a9912c4f","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2023-02-07T13:58:08Z","title_canon_sha256":"bb2bb12ae7941bbd69b225105be1858bf6e8465676f4b2503a11ffdbb8735440"},"schema_version":"1.0","source":{"id":"2302.03473","kind":"arxiv","version":1}},"canonical_sha256":"5a86d19ac1e0617e91a7c981895ca8124b392517752bba31f41804ef9b14d917","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5a86d19ac1e0617e91a7c981895ca8124b392517752bba31f41804ef9b14d917","first_computed_at":"2026-07-05T05:39:37.337725Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:39:37.337725Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jqu6dG6E69XiuLXXLGNsAw0ZeBQtDPZeGtCj3buUDR2AOswQ6CWhgZyM/oy/daCDD01KEpRa95QlQTY80vuACw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:39:37.338290Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.03473","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0dd9fc934f81fee3063d1fceced959f24e845dddac33c606b800b19626d75bcb","sha256:e45e3ea83a0ce134b33859ed3594d7ef5002275bab81f26b7ab8fd7506d1d167"],"state_sha256":"1c52b7c5ab697b22d762fcb8ae7f5b505200821ae650d65a54e1d300360c392d"}