{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:HWFUOS7B7KILAO4247XYLYTXX4","short_pith_number":"pith:HWFUOS7B","canonical_record":{"source":{"id":"2407.07841","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-10T17:00:57Z","cross_cats_sorted":[],"title_canon_sha256":"177817266e9c4a2ab3bfa501e1a226e392c60b8d6bd5f51d17576bad33fe2c64","abstract_canon_sha256":"194b6143a4d97be30142272ff30165533f96ad57cd355546bc6a6ff2ed04604b"},"schema_version":"1.0"},"canonical_sha256":"3d8b474be1fa90b03b9ae7ef85e277bf06502500bf382d19d51d2a50c04970d5","source":{"kind":"arxiv","id":"2407.07841","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.07841","created_at":"2026-07-05T09:50:32Z"},{"alias_kind":"arxiv_version","alias_value":"2407.07841v2","created_at":"2026-07-05T09:50:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.07841","created_at":"2026-07-05T09:50:32Z"},{"alias_kind":"pith_short_12","alias_value":"HWFUOS7B7KIL","created_at":"2026-07-05T09:50:32Z"},{"alias_kind":"pith_short_16","alias_value":"HWFUOS7B7KILAO42","created_at":"2026-07-05T09:50:32Z"},{"alias_kind":"pith_short_8","alias_value":"HWFUOS7B","created_at":"2026-07-05T09:50:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:HWFUOS7B7KILAO4247XYLYTXX4","target":"record","payload":{"canonical_record":{"source":{"id":"2407.07841","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-10T17:00:57Z","cross_cats_sorted":[],"title_canon_sha256":"177817266e9c4a2ab3bfa501e1a226e392c60b8d6bd5f51d17576bad33fe2c64","abstract_canon_sha256":"194b6143a4d97be30142272ff30165533f96ad57cd355546bc6a6ff2ed04604b"},"schema_version":"1.0"},"canonical_sha256":"3d8b474be1fa90b03b9ae7ef85e277bf06502500bf382d19d51d2a50c04970d5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:50:32.003097Z","signature_b64":"fO1/64Ey/depb0wHsUivhFZ2Ys4bzqQfLOi4fzT7AjX1o9o0HwSuTumFD789GPxtfaIUWZULbPrg4QEtEUgbDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3d8b474be1fa90b03b9ae7ef85e277bf06502500bf382d19d51d2a50c04970d5","last_reissued_at":"2026-07-05T09:50:32.002578Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:50:32.002578Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.07841","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":"2026-07-05T09:50:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vRh97ybLjt3GN0zzPGVk6ujeUIHWk7gx2MZcSqnIYTqc0BwOZ1tp8z/Ge/ZIJ89dtEoeYe93xoBfe5a1OEjICA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:29:27.654450Z"},"content_sha256":"3ba4338a3473becbd4d12cb7da2f431ff22a3120650c8aebbdd91b88a7ed1391","schema_version":"1.0","event_id":"sha256:3ba4338a3473becbd4d12cb7da2f431ff22a3120650c8aebbdd91b88a7ed1391"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:HWFUOS7B7KILAO4247XYLYTXX4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Benchmarking Embedding Aggregation Methods in Computational Pathology: A Clinical Data Perspective","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abdulkadir Elmas, Adam J. Schoenfeld, Alexandros D. Polydorides, Aryeh Stock, Chad Vanderbilt, Gabriele Campanella, Jane Houldsworth, Jennifer Zeng, Kuan-lin Huang, Shengjia Chen, Thomas J. Fuchs","submitted_at":"2024-07-10T17:00:57Z","abstract_excerpt":"Recent advances in artificial intelligence (AI), in particular self-supervised learning of foundation models (FMs), are revolutionizing medical imaging and computational pathology (CPath). A constant challenge in the analysis of digital Whole Slide Images (WSIs) is the problem of aggregating tens of thousands of tile-level image embeddings to a slide-level representation. Due to the prevalent use of datasets created for genomic research, such as TCGA, for method development, the performance of these techniques on diagnostic slides from clinical practice has been inadequately explored. This stu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.07841","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/2407.07841/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":"2026-07-05T09:50:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7VEM4lD1/QWGXfyvy4Q55Og8O3KriVpRyaZsAqfLrc7+iK0mv122GLPOkEFzWfqmar0PEcDu641RuIPBan3ACQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:29:27.654943Z"},"content_sha256":"b23b39eaa180b2864a1351d7a576ad28c26c36162c1020f2fbabf18c08ea560e","schema_version":"1.0","event_id":"sha256:b23b39eaa180b2864a1351d7a576ad28c26c36162c1020f2fbabf18c08ea560e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HWFUOS7B7KILAO4247XYLYTXX4/bundle.json","state_url":"https://pith.science/pith/HWFUOS7B7KILAO4247XYLYTXX4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HWFUOS7B7KILAO4247XYLYTXX4/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":"2026-08-03T17:29:27Z","links":{"resolver":"https://pith.science/pith/HWFUOS7B7KILAO4247XYLYTXX4","bundle":"https://pith.science/pith/HWFUOS7B7KILAO4247XYLYTXX4/bundle.json","state":"https://pith.science/pith/HWFUOS7B7KILAO4247XYLYTXX4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HWFUOS7B7KILAO4247XYLYTXX4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HWFUOS7B7KILAO4247XYLYTXX4","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":"194b6143a4d97be30142272ff30165533f96ad57cd355546bc6a6ff2ed04604b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-10T17:00:57Z","title_canon_sha256":"177817266e9c4a2ab3bfa501e1a226e392c60b8d6bd5f51d17576bad33fe2c64"},"schema_version":"1.0","source":{"id":"2407.07841","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.07841","created_at":"2026-07-05T09:50:32Z"},{"alias_kind":"arxiv_version","alias_value":"2407.07841v2","created_at":"2026-07-05T09:50:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.07841","created_at":"2026-07-05T09:50:32Z"},{"alias_kind":"pith_short_12","alias_value":"HWFUOS7B7KIL","created_at":"2026-07-05T09:50:32Z"},{"alias_kind":"pith_short_16","alias_value":"HWFUOS7B7KILAO42","created_at":"2026-07-05T09:50:32Z"},{"alias_kind":"pith_short_8","alias_value":"HWFUOS7B","created_at":"2026-07-05T09:50:32Z"}],"graph_snapshots":[{"event_id":"sha256:b23b39eaa180b2864a1351d7a576ad28c26c36162c1020f2fbabf18c08ea560e","target":"graph","created_at":"2026-07-05T09:50:32Z","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/2407.07841/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advances in artificial intelligence (AI), in particular self-supervised learning of foundation models (FMs), are revolutionizing medical imaging and computational pathology (CPath). A constant challenge in the analysis of digital Whole Slide Images (WSIs) is the problem of aggregating tens of thousands of tile-level image embeddings to a slide-level representation. Due to the prevalent use of datasets created for genomic research, such as TCGA, for method development, the performance of these techniques on diagnostic slides from clinical practice has been inadequately explored. This stu","authors_text":"Abdulkadir Elmas, Adam J. Schoenfeld, Alexandros D. Polydorides, Aryeh Stock, Chad Vanderbilt, Gabriele Campanella, Jane Houldsworth, Jennifer Zeng, Kuan-lin Huang, Shengjia Chen, Thomas J. Fuchs","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-10T17:00:57Z","title":"Benchmarking Embedding Aggregation Methods in Computational Pathology: A Clinical Data Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.07841","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":"sha256:3ba4338a3473becbd4d12cb7da2f431ff22a3120650c8aebbdd91b88a7ed1391","target":"record","created_at":"2026-07-05T09:50:32Z","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":"194b6143a4d97be30142272ff30165533f96ad57cd355546bc6a6ff2ed04604b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-10T17:00:57Z","title_canon_sha256":"177817266e9c4a2ab3bfa501e1a226e392c60b8d6bd5f51d17576bad33fe2c64"},"schema_version":"1.0","source":{"id":"2407.07841","kind":"arxiv","version":2}},"canonical_sha256":"3d8b474be1fa90b03b9ae7ef85e277bf06502500bf382d19d51d2a50c04970d5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3d8b474be1fa90b03b9ae7ef85e277bf06502500bf382d19d51d2a50c04970d5","first_computed_at":"2026-07-05T09:50:32.002578Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:50:32.002578Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fO1/64Ey/depb0wHsUivhFZ2Ys4bzqQfLOi4fzT7AjX1o9o0HwSuTumFD789GPxtfaIUWZULbPrg4QEtEUgbDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:50:32.003097Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.07841","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3ba4338a3473becbd4d12cb7da2f431ff22a3120650c8aebbdd91b88a7ed1391","sha256:b23b39eaa180b2864a1351d7a576ad28c26c36162c1020f2fbabf18c08ea560e"],"state_sha256":"e53df0abea0a8aa8419737dc02a0e8818943becefdb444db9728a74bd3e2e0f6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LzFOYvb9zcPYFDhMuHWKMpy8Sg3JTCin924hc1LNJjDaRqPFF13BDA6k6rLCBsKVQVS0TtyBTJXLmR8HEv9zDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T17:29:27.658964Z","bundle_sha256":"48e461f518e244e539a99aae64b66651553de6297f2176d871474bf3694853f3"}}