{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:3WKN77QD5DAPVFJ3JF3CTYRCSM","short_pith_number":"pith:3WKN77QD","canonical_record":{"source":{"id":"1806.04972","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-13T12:15:54Z","cross_cats_sorted":[],"title_canon_sha256":"f4340324ce286e068bcdc426a2e705b06a74ccb2734f01888202c64edcefa6ea","abstract_canon_sha256":"c2f8e88986b337c6113a204f5e12c71f8132ee499da1d4a2ea9cbffbc2492556"},"schema_version":"1.0"},"canonical_sha256":"dd94dffe03e8c0fa953b497629e22293052466d22170009d607e1fd567880b3e","source":{"kind":"arxiv","id":"1806.04972","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.04972","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"arxiv_version","alias_value":"1806.04972v1","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.04972","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"pith_short_12","alias_value":"3WKN77QD5DAP","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_16","alias_value":"3WKN77QD5DAPVFJ3","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_8","alias_value":"3WKN77QD","created_at":"2026-05-18T12:32:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:3WKN77QD5DAPVFJ3JF3CTYRCSM","target":"record","payload":{"canonical_record":{"source":{"id":"1806.04972","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-13T12:15:54Z","cross_cats_sorted":[],"title_canon_sha256":"f4340324ce286e068bcdc426a2e705b06a74ccb2734f01888202c64edcefa6ea","abstract_canon_sha256":"c2f8e88986b337c6113a204f5e12c71f8132ee499da1d4a2ea9cbffbc2492556"},"schema_version":"1.0"},"canonical_sha256":"dd94dffe03e8c0fa953b497629e22293052466d22170009d607e1fd567880b3e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:13:20.428080Z","signature_b64":"SyfNsmqK4HcTGsk0rubB2CiuSH+nbS8mxEnGOH6t4tXiT4z9+hpZyB78RvT8cu0mQiRSD14UGMTheXngsui9Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dd94dffe03e8c0fa953b497629e22293052466d22170009d607e1fd567880b3e","last_reissued_at":"2026-05-18T00:13:20.427481Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:13:20.427481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.04972","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":"2026-05-18T00:13:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wfA78NPS64kze27LK2k1y6XEUmE0+o7+Olg+hT94mnzIm9XquKdy3ij5tEaQxwQANqHUcPc7BuTNMn10iS6nCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T21:06:51.703446Z"},"content_sha256":"d4ab2418973a36332a8314bd4ba20c5f341acc388e64c079c793ef78ad490030","schema_version":"1.0","event_id":"sha256:d4ab2418973a36332a8314bd4ba20c5f341acc388e64c079c793ef78ad490030"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:3WKN77QD5DAPVFJ3JF3CTYRCSM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Detection of Lesions in Brain MRI using constrained adversarial auto-encoders","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ender Konukoglu, Xiaoran Chen","submitted_at":"2018-06-13T12:15:54Z","abstract_excerpt":"Lesion detection in brain Magnetic Resonance Images (MRI) remains a challenging task. State-of-the-art approaches are mostly based on supervised learning making use of large annotated datasets. Human beings, on the other hand, even non-experts, can detect most abnormal lesions after seeing a handful of healthy brain images. Replicating this capability of using prior information on the appearance of healthy brain structure to detect lesions can help computers achieve human level abnormality detection, specifically reducing the need for numerous labeled examples and bettering generalization of p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.04972","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":""},"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":"2026-05-18T00:13:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qA3amgJRZ+/sbuVIeO2wiWkeTEEQPTudBMhb5Thf3MHa4TcIkPRAdePOkoWi1B2LcSj4eW2NP7hxqUOkpvWBBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T21:06:51.704251Z"},"content_sha256":"915ec99a74b3045b0e448e60ccd5a05d35e809d2d69a7d4581177a6bb231871c","schema_version":"1.0","event_id":"sha256:915ec99a74b3045b0e448e60ccd5a05d35e809d2d69a7d4581177a6bb231871c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3WKN77QD5DAPVFJ3JF3CTYRCSM/bundle.json","state_url":"https://pith.science/pith/3WKN77QD5DAPVFJ3JF3CTYRCSM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3WKN77QD5DAPVFJ3JF3CTYRCSM/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":"2026-05-31T21:06:51Z","links":{"resolver":"https://pith.science/pith/3WKN77QD5DAPVFJ3JF3CTYRCSM","bundle":"https://pith.science/pith/3WKN77QD5DAPVFJ3JF3CTYRCSM/bundle.json","state":"https://pith.science/pith/3WKN77QD5DAPVFJ3JF3CTYRCSM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3WKN77QD5DAPVFJ3JF3CTYRCSM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:3WKN77QD5DAPVFJ3JF3CTYRCSM","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":"c2f8e88986b337c6113a204f5e12c71f8132ee499da1d4a2ea9cbffbc2492556","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-13T12:15:54Z","title_canon_sha256":"f4340324ce286e068bcdc426a2e705b06a74ccb2734f01888202c64edcefa6ea"},"schema_version":"1.0","source":{"id":"1806.04972","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.04972","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"arxiv_version","alias_value":"1806.04972v1","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.04972","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"pith_short_12","alias_value":"3WKN77QD5DAP","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_16","alias_value":"3WKN77QD5DAPVFJ3","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_8","alias_value":"3WKN77QD","created_at":"2026-05-18T12:32:05Z"}],"graph_snapshots":[{"event_id":"sha256:915ec99a74b3045b0e448e60ccd5a05d35e809d2d69a7d4581177a6bb231871c","target":"graph","created_at":"2026-05-18T00:13:20Z","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"},"paper":{"abstract_excerpt":"Lesion detection in brain Magnetic Resonance Images (MRI) remains a challenging task. State-of-the-art approaches are mostly based on supervised learning making use of large annotated datasets. Human beings, on the other hand, even non-experts, can detect most abnormal lesions after seeing a handful of healthy brain images. Replicating this capability of using prior information on the appearance of healthy brain structure to detect lesions can help computers achieve human level abnormality detection, specifically reducing the need for numerous labeled examples and bettering generalization of p","authors_text":"Ender Konukoglu, Xiaoran Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-13T12:15:54Z","title":"Unsupervised Detection of Lesions in Brain MRI using constrained adversarial auto-encoders"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.04972","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:d4ab2418973a36332a8314bd4ba20c5f341acc388e64c079c793ef78ad490030","target":"record","created_at":"2026-05-18T00:13:20Z","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":"c2f8e88986b337c6113a204f5e12c71f8132ee499da1d4a2ea9cbffbc2492556","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-13T12:15:54Z","title_canon_sha256":"f4340324ce286e068bcdc426a2e705b06a74ccb2734f01888202c64edcefa6ea"},"schema_version":"1.0","source":{"id":"1806.04972","kind":"arxiv","version":1}},"canonical_sha256":"dd94dffe03e8c0fa953b497629e22293052466d22170009d607e1fd567880b3e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dd94dffe03e8c0fa953b497629e22293052466d22170009d607e1fd567880b3e","first_computed_at":"2026-05-18T00:13:20.427481Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:13:20.427481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SyfNsmqK4HcTGsk0rubB2CiuSH+nbS8mxEnGOH6t4tXiT4z9+hpZyB78RvT8cu0mQiRSD14UGMTheXngsui9Cg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:13:20.428080Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.04972","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d4ab2418973a36332a8314bd4ba20c5f341acc388e64c079c793ef78ad490030","sha256:915ec99a74b3045b0e448e60ccd5a05d35e809d2d69a7d4581177a6bb231871c"],"state_sha256":"eb7bf8c234438e7325cb07d965235ab2c423b57739a602db771434687d3ba973"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2LROQshGeVyqeWZScSz25F2+G/DNPZyKkWCVuLx/jK/BvcpntqlelKxaenMb2l06l0mxIKYl9uBSfyWf7XgyAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T21:06:51.708302Z","bundle_sha256":"ef78c505a089f1cd9c3299501866cfcc5a073b29eb1cb3bd9b9b4de62f70380b"}}