{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:ITR6PPWDW2ADVDDY43AMKJ5MIA","short_pith_number":"pith:ITR6PPWD","canonical_record":{"source":{"id":"2005.14635","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-05-29T15:52:48Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"53140dd65d24a107ede4bb7dcdc2f4bdf6b27db139f710d55614640677504c00","abstract_canon_sha256":"4e8972d26574f9a8c535089585bc29e6323c8753e34c7351ddec5169b6735027"},"schema_version":"1.0"},"canonical_sha256":"44e3e7bec3b6803a8c78e6c0c527ac403322571aaa6df7f0628d55bb76f7ab20","source":{"kind":"arxiv","id":"2005.14635","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.14635","created_at":"2026-07-05T03:19:58Z"},{"alias_kind":"arxiv_version","alias_value":"2005.14635v2","created_at":"2026-07-05T03:19:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.14635","created_at":"2026-07-05T03:19:58Z"},{"alias_kind":"pith_short_12","alias_value":"ITR6PPWDW2AD","created_at":"2026-07-05T03:19:58Z"},{"alias_kind":"pith_short_16","alias_value":"ITR6PPWDW2ADVDDY","created_at":"2026-07-05T03:19:58Z"},{"alias_kind":"pith_short_8","alias_value":"ITR6PPWD","created_at":"2026-07-05T03:19:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:ITR6PPWDW2ADVDDY43AMKJ5MIA","target":"record","payload":{"canonical_record":{"source":{"id":"2005.14635","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-05-29T15:52:48Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"53140dd65d24a107ede4bb7dcdc2f4bdf6b27db139f710d55614640677504c00","abstract_canon_sha256":"4e8972d26574f9a8c535089585bc29e6323c8753e34c7351ddec5169b6735027"},"schema_version":"1.0"},"canonical_sha256":"44e3e7bec3b6803a8c78e6c0c527ac403322571aaa6df7f0628d55bb76f7ab20","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:19:58.845307Z","signature_b64":"ucWUedsvaUUfCbqubjNSc8hltpuLgNUEM3hp5+FbAtt5JnB/IgJVXFHrKsCPUo04C+5kBHsJxnt139l1w0MkDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"44e3e7bec3b6803a8c78e6c0c527ac403322571aaa6df7f0628d55bb76f7ab20","last_reissued_at":"2026-07-05T03:19:58.844860Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:19:58.844860Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2005.14635","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":"2026-07-05T03:19:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2yIXSd0gU/BvBUbMdJs04WFpXSbMkJNfadCNZe+kO9ESDqnEkKQ5jHJFvo7eHglSAeQNW9C4RH3Xwy4DZsaPDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T23:55:10.047284Z"},"content_sha256":"8578b378f2b92acf3f306e66cf0184711b600c3d9aa1928781219ed0bfaeb8ca","schema_version":"1.0","event_id":"sha256:8578b378f2b92acf3f306e66cf0184711b600c3d9aa1928781219ed0bfaeb8ca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:ITR6PPWDW2ADVDDY43AMKJ5MIA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"David Apar\\'icio, Joana Lorenz, Jo\\~ao Tiago Ascens\\~ao, Maria In\\^es Silva, Pedro Bizarro","submitted_at":"2020-05-29T15:52:48Z","abstract_excerpt":"Every year, criminals launder billions of dollars acquired from serious felonies (e.g., terrorism, drug smuggling, or human trafficking) harming countless people and economies. Cryptocurrencies, in particular, have developed as a haven for money laundering activity. Machine Learning can be used to detect these illicit patterns. However, labels are so scarce that traditional supervised algorithms are inapplicable. Here, we address money laundering detection assuming minimal access to labels. First, we show that existing state-of-the-art solutions using unsupervised anomaly detection methods are"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.14635","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/2005.14635/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":"2026-07-05T03:19:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nD//7a0VCJG978Q/LoAz5WIWmCrVGQxqpvkZfLxQvH6usH3I6Nf8ZEmlrMBTHsjjivtWzAx0Z74R7FyNtJO7Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T23:55:10.047772Z"},"content_sha256":"ed1e53cfec02451aa54ec649b229881781ad3f958795f1e2e57147d35590e6dd","schema_version":"1.0","event_id":"sha256:ed1e53cfec02451aa54ec649b229881781ad3f958795f1e2e57147d35590e6dd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ITR6PPWDW2ADVDDY43AMKJ5MIA/bundle.json","state_url":"https://pith.science/pith/ITR6PPWDW2ADVDDY43AMKJ5MIA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ITR6PPWDW2ADVDDY43AMKJ5MIA/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":"2026-08-05T23:55:10Z","links":{"resolver":"https://pith.science/pith/ITR6PPWDW2ADVDDY43AMKJ5MIA","bundle":"https://pith.science/pith/ITR6PPWDW2ADVDDY43AMKJ5MIA/bundle.json","state":"https://pith.science/pith/ITR6PPWDW2ADVDDY43AMKJ5MIA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ITR6PPWDW2ADVDDY43AMKJ5MIA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:ITR6PPWDW2ADVDDY43AMKJ5MIA","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":"4e8972d26574f9a8c535089585bc29e6323c8753e34c7351ddec5169b6735027","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-05-29T15:52:48Z","title_canon_sha256":"53140dd65d24a107ede4bb7dcdc2f4bdf6b27db139f710d55614640677504c00"},"schema_version":"1.0","source":{"id":"2005.14635","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.14635","created_at":"2026-07-05T03:19:58Z"},{"alias_kind":"arxiv_version","alias_value":"2005.14635v2","created_at":"2026-07-05T03:19:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.14635","created_at":"2026-07-05T03:19:58Z"},{"alias_kind":"pith_short_12","alias_value":"ITR6PPWDW2AD","created_at":"2026-07-05T03:19:58Z"},{"alias_kind":"pith_short_16","alias_value":"ITR6PPWDW2ADVDDY","created_at":"2026-07-05T03:19:58Z"},{"alias_kind":"pith_short_8","alias_value":"ITR6PPWD","created_at":"2026-07-05T03:19:58Z"}],"graph_snapshots":[{"event_id":"sha256:ed1e53cfec02451aa54ec649b229881781ad3f958795f1e2e57147d35590e6dd","target":"graph","created_at":"2026-07-05T03:19:58Z","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/2005.14635/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Every year, criminals launder billions of dollars acquired from serious felonies (e.g., terrorism, drug smuggling, or human trafficking) harming countless people and economies. Cryptocurrencies, in particular, have developed as a haven for money laundering activity. Machine Learning can be used to detect these illicit patterns. However, labels are so scarce that traditional supervised algorithms are inapplicable. Here, we address money laundering detection assuming minimal access to labels. First, we show that existing state-of-the-art solutions using unsupervised anomaly detection methods are","authors_text":"David Apar\\'icio, Joana Lorenz, Jo\\~ao Tiago Ascens\\~ao, Maria In\\^es Silva, Pedro Bizarro","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-05-29T15:52:48Z","title":"Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.14635","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":"sha256:8578b378f2b92acf3f306e66cf0184711b600c3d9aa1928781219ed0bfaeb8ca","target":"record","created_at":"2026-07-05T03:19:58Z","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":"4e8972d26574f9a8c535089585bc29e6323c8753e34c7351ddec5169b6735027","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-05-29T15:52:48Z","title_canon_sha256":"53140dd65d24a107ede4bb7dcdc2f4bdf6b27db139f710d55614640677504c00"},"schema_version":"1.0","source":{"id":"2005.14635","kind":"arxiv","version":2}},"canonical_sha256":"44e3e7bec3b6803a8c78e6c0c527ac403322571aaa6df7f0628d55bb76f7ab20","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"44e3e7bec3b6803a8c78e6c0c527ac403322571aaa6df7f0628d55bb76f7ab20","first_computed_at":"2026-07-05T03:19:58.844860Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:19:58.844860Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ucWUedsvaUUfCbqubjNSc8hltpuLgNUEM3hp5+FbAtt5JnB/IgJVXFHrKsCPUo04C+5kBHsJxnt139l1w0MkDw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:19:58.845307Z","signed_message":"canonical_sha256_bytes"},"source_id":"2005.14635","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8578b378f2b92acf3f306e66cf0184711b600c3d9aa1928781219ed0bfaeb8ca","sha256:ed1e53cfec02451aa54ec649b229881781ad3f958795f1e2e57147d35590e6dd"],"state_sha256":"61a6b758ff928f8fd49118e3225311e8a292427b83d81a49726c9bb33e201226"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b7yaGikIXmPMOkek6Hx7L1a4B2dB08sNjg4kj0B9eBRq4ZohPBrFamuWcXUKY82uHwvEUySm45x+M9cwWgbxAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T23:55:10.051150Z","bundle_sha256":"3d32243ce649085607c529eff5659f84f3e60608054c8e6020d8ef500421c080"}}