{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:PAXJM26DARLI7JARSH3JCH5TFO","short_pith_number":"pith:PAXJM26D","schema_version":"1.0","canonical_sha256":"782e966bc304568fa41191f6911fb32b94d4ce1ca78cc45f173c858188225d73","source":{"kind":"arxiv","id":"2003.00086","version":1},"attestation_state":"computed","paper":{"title":"Constrained Generative Adversarial Network Ensembles for Sharable Synthetic Data Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"Barbaros Selnur Erdal, Engin Dikici, Luciano M. Prevedello, Matthew Bigelow, Richard D. White","submitted_at":"2020-02-28T22:03:27Z","abstract_excerpt":"The sharing of medical imaging datasets between institutions, and even inside the same institution, is limited by various regulations/legal barriers. Although these limitations are necessities for protecting patient privacy and setting strict boundaries for data ownership, medical research projects that require large datasets suffer considerably as a result. Machine learning has been revolutionized with the emerging deep neural network approaches over recent years, making the data-related limitations even a larger problem as these novel techniques commonly require immense imaging datasets. Thi"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2003.00086","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-02-28T22:03:27Z","cross_cats_sorted":[],"title_canon_sha256":"e065abebda3a3d7acf3df40f03804d57d1e79f63290b90fa605968e117798a41","abstract_canon_sha256":"b09dfa466b3886f637c3b91e04341483eeb55b40500176190694ef2297d4bf6b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:44:44.007473Z","signature_b64":"TAANvaxTt8dZFJjIyd3OEVtkmYY0svzTXJuyOCOSbY8tDOASPjlQrhqSF9IBHSyiSPhUT7cHax0HdTd/FXzOAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"782e966bc304568fa41191f6911fb32b94d4ce1ca78cc45f173c858188225d73","last_reissued_at":"2026-07-05T00:44:44.007116Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:44:44.007116Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Constrained Generative Adversarial Network Ensembles for Sharable Synthetic Data Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"Barbaros Selnur Erdal, Engin Dikici, Luciano M. Prevedello, Matthew Bigelow, Richard D. White","submitted_at":"2020-02-28T22:03:27Z","abstract_excerpt":"The sharing of medical imaging datasets between institutions, and even inside the same institution, is limited by various regulations/legal barriers. Although these limitations are necessities for protecting patient privacy and setting strict boundaries for data ownership, medical research projects that require large datasets suffer considerably as a result. Machine learning has been revolutionized with the emerging deep neural network approaches over recent years, making the data-related limitations even a larger problem as these novel techniques commonly require immense imaging datasets. Thi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.00086","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/2003.00086/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2003.00086","created_at":"2026-07-05T00:44:44.007179+00:00"},{"alias_kind":"arxiv_version","alias_value":"2003.00086v1","created_at":"2026-07-05T00:44:44.007179+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.00086","created_at":"2026-07-05T00:44:44.007179+00:00"},{"alias_kind":"pith_short_12","alias_value":"PAXJM26DARLI","created_at":"2026-07-05T00:44:44.007179+00:00"},{"alias_kind":"pith_short_16","alias_value":"PAXJM26DARLI7JAR","created_at":"2026-07-05T00:44:44.007179+00:00"},{"alias_kind":"pith_short_8","alias_value":"PAXJM26D","created_at":"2026-07-05T00:44:44.007179+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PAXJM26DARLI7JARSH3JCH5TFO","json":"https://pith.science/pith/PAXJM26DARLI7JARSH3JCH5TFO.json","graph_json":"https://pith.science/api/pith-number/PAXJM26DARLI7JARSH3JCH5TFO/graph.json","events_json":"https://pith.science/api/pith-number/PAXJM26DARLI7JARSH3JCH5TFO/events.json","paper":"https://pith.science/paper/PAXJM26D"},"agent_actions":{"view_html":"https://pith.science/pith/PAXJM26DARLI7JARSH3JCH5TFO","download_json":"https://pith.science/pith/PAXJM26DARLI7JARSH3JCH5TFO.json","view_paper":"https://pith.science/paper/PAXJM26D","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2003.00086&json=true","fetch_graph":"https://pith.science/api/pith-number/PAXJM26DARLI7JARSH3JCH5TFO/graph.json","fetch_events":"https://pith.science/api/pith-number/PAXJM26DARLI7JARSH3JCH5TFO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PAXJM26DARLI7JARSH3JCH5TFO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PAXJM26DARLI7JARSH3JCH5TFO/action/storage_attestation","attest_author":"https://pith.science/pith/PAXJM26DARLI7JARSH3JCH5TFO/action/author_attestation","sign_citation":"https://pith.science/pith/PAXJM26DARLI7JARSH3JCH5TFO/action/citation_signature","submit_replication":"https://pith.science/pith/PAXJM26DARLI7JARSH3JCH5TFO/action/replication_record"}},"created_at":"2026-07-05T00:44:44.007179+00:00","updated_at":"2026-07-05T00:44:44.007179+00:00"}