{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:AYAS4ZVGYTMRIUGRF2H5SI55QF","short_pith_number":"pith:AYAS4ZVG","canonical_record":{"source":{"id":"2608.00586","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-01T10:53:26Z","cross_cats_sorted":[],"title_canon_sha256":"5c5df860cc07f064238e8893d0fa64f5a40bbc9246227a2c8abf6db1ed50aa5c","abstract_canon_sha256":"4198e9499709f605fb30e3d750b320891dd20579e1beb2c2f44eca8bbc7d119e"},"schema_version":"1.0"},"canonical_sha256":"06012e66a6c4d91450d12e8fd923bd814cf57e4d036e06b9e74e3b88346ae7b5","source":{"kind":"arxiv","id":"2608.00586","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.00586","created_at":"2026-08-04T00:37:41Z"},{"alias_kind":"arxiv_version","alias_value":"2608.00586v1","created_at":"2026-08-04T00:37:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.00586","created_at":"2026-08-04T00:37:41Z"},{"alias_kind":"pith_short_12","alias_value":"AYAS4ZVGYTMR","created_at":"2026-08-04T00:37:41Z"},{"alias_kind":"pith_short_16","alias_value":"AYAS4ZVGYTMRIUGR","created_at":"2026-08-04T00:37:41Z"},{"alias_kind":"pith_short_8","alias_value":"AYAS4ZVG","created_at":"2026-08-04T00:37:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:AYAS4ZVGYTMRIUGRF2H5SI55QF","target":"record","payload":{"canonical_record":{"source":{"id":"2608.00586","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-01T10:53:26Z","cross_cats_sorted":[],"title_canon_sha256":"5c5df860cc07f064238e8893d0fa64f5a40bbc9246227a2c8abf6db1ed50aa5c","abstract_canon_sha256":"4198e9499709f605fb30e3d750b320891dd20579e1beb2c2f44eca8bbc7d119e"},"schema_version":"1.0"},"canonical_sha256":"06012e66a6c4d91450d12e8fd923bd814cf57e4d036e06b9e74e3b88346ae7b5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-04T00:37:41.752230Z","signature_b64":"ufwjFhEGt5VqpvfiiFk83jB1/D3zoV2qnY1ZLN9k3vMxWc/quJB/XjsV2HY4ph6t5BjYC3wJQPqoWS6dgJLnAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"06012e66a6c4d91450d12e8fd923bd814cf57e4d036e06b9e74e3b88346ae7b5","last_reissued_at":"2026-08-04T00:37:41.750705Z","signature_status":"signed_v1","first_computed_at":"2026-08-04T00:37:41.750705Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.00586","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":"2026-08-04T00:37:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wJuKz1++QelyMVWBLLZNOFfZQmC+M4mrL/AoraPQRdBns7u1gha/Gpn2vEjIbwvxo1GDjXRKQdk6Rntb+t3qBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T04:24:10.549636Z"},"content_sha256":"91dc48cb3855e2a68264b0eb61c0d4f9934d4d88e1069e696e692713e1dee7b8","schema_version":"1.0","event_id":"sha256:91dc48cb3855e2a68264b0eb61c0d4f9934d4d88e1069e696e692713e1dee7b8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:AYAS4ZVGYTMRIUGRF2H5SI55QF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Representation Transfer of Foundation Models for Ultra-Widefield Retinal Imaging","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Da Ma, Ivana Matovinovic, Lovre Antonio Budimir, Marinko V. Sarunic, Mingya Alexa Gong, Myeong Jin Ju, Pearse A. Keane, Siegfried K. Wagner, Sven Loncaric, Yukun Zhou","submitted_at":"2026-08-01T10:53:26Z","abstract_excerpt":"Despite the widespread adoption of foundation models as feature extractors for medical imaging, relatively little is understood about how different pretraining strategies influence the transferability of learned representations to weakly supervised ophthalmic imaging tasks. We investigate this question in ultra-widefield (UWF) retinal imaging by evaluating foundation model representations within a patch-based multiple instance learning (MIL) framework for disease classification on UWF images. We compare Vision Transformer encoders pretrained with supervised, Masked Autoencoder (MAE), and self-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.00586","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/2608.00586/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":"2026-08-04T00:37:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mh9vtgV6ztZpmISbJ8wyIHvmnzyTEeMAFR8jXH6U+cu+zPtoeDJc2Gmr6jmj+ZD9rDeG8oDyI3H2T1+dpc0HCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T04:24:10.550366Z"},"content_sha256":"5005991a069ecae8f9bd14cfb4fcc08a9d0d45d7c9791b12d8bc2d20c87a9d63","schema_version":"1.0","event_id":"sha256:5005991a069ecae8f9bd14cfb4fcc08a9d0d45d7c9791b12d8bc2d20c87a9d63"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:AYAS4ZVGYTMRIUGRF2H5SI55QF","target":"integrity","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1186/s12911-024-02446-x) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"S. V . Chilukoti, L. Shan, V . S. Tida, A. S. Maida, and X. Hei, ‘‘A reliable diabetic retinopathy grading via transfer learning and ensemble learning with quadratic weighted kappa metric,’’BMC Med. Inform. Decis. Mak., vol. 24, no. 1, Art.","arxiv_id":"2608.00586","detector":"doi_compliance","evidence":{"ref_index":32,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"10.1186/s12911-","reconstructed_doi":"10.1186/s12911-024-02446-x"},"severity":"advisory","ref_index":32,"audited_at":"2026-08-05T00:39:00.418078Z","event_type":"pith.integrity.v1","detected_doi":"10.1186/s12911-024-02446-x","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"a650329646a3f7fda9f7bbb3a79a688e7f38fd541fac93008957cd0d13e27cb4","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":17993,"payload_sha256":"ba483fde256f6c01727708d35ac7fbab2715180b8368e22985dd1ac7cb80e1bc","signature_b64":"rR7/ORf6QwDQQtDX1uq4G0EYyQnsidO0HcTA+81PHpNzXrR7FC/gRrOK+nLzKfRdMmIwvkxD4zsXl8qUSynQDw==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-05T00:43:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+zUsVrb2JCzGguw/VU+zgNUZaF8Q5ri8VEpPYGWoETknOv3lFP3Pkzm1wa27QMtyxMhfgmTWhWmXrnkgnIxZDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T04:24:10.553019Z"},"content_sha256":"a7324fb7ccdf6d611db83a3d15acde033ca21eb4f299dfd3dec7eb1cf0c48509","schema_version":"1.0","event_id":"sha256:a7324fb7ccdf6d611db83a3d15acde033ca21eb4f299dfd3dec7eb1cf0c48509"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AYAS4ZVGYTMRIUGRF2H5SI55QF/bundle.json","state_url":"https://pith.science/pith/AYAS4ZVGYTMRIUGRF2H5SI55QF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AYAS4ZVGYTMRIUGRF2H5SI55QF/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":"2026-08-06T04:24:10Z","links":{"resolver":"https://pith.science/pith/AYAS4ZVGYTMRIUGRF2H5SI55QF","bundle":"https://pith.science/pith/AYAS4ZVGYTMRIUGRF2H5SI55QF/bundle.json","state":"https://pith.science/pith/AYAS4ZVGYTMRIUGRF2H5SI55QF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AYAS4ZVGYTMRIUGRF2H5SI55QF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:AYAS4ZVGYTMRIUGRF2H5SI55QF","merge_version":"pith-open-graph-merge-v1","event_count":3,"valid_event_count":3,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"4198e9499709f605fb30e3d750b320891dd20579e1beb2c2f44eca8bbc7d119e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-01T10:53:26Z","title_canon_sha256":"5c5df860cc07f064238e8893d0fa64f5a40bbc9246227a2c8abf6db1ed50aa5c"},"schema_version":"1.0","source":{"id":"2608.00586","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.00586","created_at":"2026-08-04T00:37:41Z"},{"alias_kind":"arxiv_version","alias_value":"2608.00586v1","created_at":"2026-08-04T00:37:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.00586","created_at":"2026-08-04T00:37:41Z"},{"alias_kind":"pith_short_12","alias_value":"AYAS4ZVGYTMR","created_at":"2026-08-04T00:37:41Z"},{"alias_kind":"pith_short_16","alias_value":"AYAS4ZVGYTMRIUGR","created_at":"2026-08-04T00:37:41Z"},{"alias_kind":"pith_short_8","alias_value":"AYAS4ZVG","created_at":"2026-08-04T00:37:41Z"}],"graph_snapshots":[{"event_id":"sha256:5005991a069ecae8f9bd14cfb4fcc08a9d0d45d7c9791b12d8bc2d20c87a9d63","target":"graph","created_at":"2026-08-04T00:37:41Z","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/2608.00586/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite the widespread adoption of foundation models as feature extractors for medical imaging, relatively little is understood about how different pretraining strategies influence the transferability of learned representations to weakly supervised ophthalmic imaging tasks. We investigate this question in ultra-widefield (UWF) retinal imaging by evaluating foundation model representations within a patch-based multiple instance learning (MIL) framework for disease classification on UWF images. We compare Vision Transformer encoders pretrained with supervised, Masked Autoencoder (MAE), and self-","authors_text":"Da Ma, Ivana Matovinovic, Lovre Antonio Budimir, Marinko V. Sarunic, Mingya Alexa Gong, Myeong Jin Ju, Pearse A. Keane, Siegfried K. Wagner, Sven Loncaric, Yukun Zhou","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-01T10:53:26Z","title":"Representation Transfer of Foundation Models for Ultra-Widefield Retinal Imaging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.00586","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":"sha256:91dc48cb3855e2a68264b0eb61c0d4f9934d4d88e1069e696e692713e1dee7b8","target":"record","created_at":"2026-08-04T00:37:41Z","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":"4198e9499709f605fb30e3d750b320891dd20579e1beb2c2f44eca8bbc7d119e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-08-01T10:53:26Z","title_canon_sha256":"5c5df860cc07f064238e8893d0fa64f5a40bbc9246227a2c8abf6db1ed50aa5c"},"schema_version":"1.0","source":{"id":"2608.00586","kind":"arxiv","version":1}},"canonical_sha256":"06012e66a6c4d91450d12e8fd923bd814cf57e4d036e06b9e74e3b88346ae7b5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"06012e66a6c4d91450d12e8fd923bd814cf57e4d036e06b9e74e3b88346ae7b5","first_computed_at":"2026-08-04T00:37:41.750705Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-04T00:37:41.750705Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ufwjFhEGt5VqpvfiiFk83jB1/D3zoV2qnY1ZLN9k3vMxWc/quJB/XjsV2HY4ph6t5BjYC3wJQPqoWS6dgJLnAQ==","signature_status":"signed_v1","signed_at":"2026-08-04T00:37:41.752230Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.00586","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:91dc48cb3855e2a68264b0eb61c0d4f9934d4d88e1069e696e692713e1dee7b8","sha256:5005991a069ecae8f9bd14cfb4fcc08a9d0d45d7c9791b12d8bc2d20c87a9d63","sha256:a7324fb7ccdf6d611db83a3d15acde033ca21eb4f299dfd3dec7eb1cf0c48509"],"state_sha256":"de500cf3483c7c725029ac1d7a2fc66132230f31dc983acdc09fcde0ce43f9e1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tOvyYZ6YOr2H8br6nQJUF3kcB2hqt3ClOoCZJL560GOKnT3D3zEWnD4QceSi3fMsVFG81C28whfmjwvUz4dkDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T04:24:10.555351Z","bundle_sha256":"93a96a59e899bf5ffbb88e9dc33292941508dc789cc7e44fbc8922884052de6a"}}