{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:NEAREU7U2XPMRNLQHAWGF5DTLF","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":"4e8da37e52780a9d72c0ee3ca2638cbe9aad173f3742358916f023f5f68a4f11","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2021-09-22T23:18:59Z","title_canon_sha256":"9f625acca0984dab9a9cf6e4af029b21949dc2d2ec33782f7470fb6a78daabf4"},"schema_version":"1.0","source":{"id":"2109.13862","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.13862","created_at":"2026-07-05T03:18:07Z"},{"alias_kind":"arxiv_version","alias_value":"2109.13862v1","created_at":"2026-07-05T03:18:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.13862","created_at":"2026-07-05T03:18:07Z"},{"alias_kind":"pith_short_12","alias_value":"NEAREU7U2XPM","created_at":"2026-07-05T03:18:07Z"},{"alias_kind":"pith_short_16","alias_value":"NEAREU7U2XPMRNLQ","created_at":"2026-07-05T03:18:07Z"},{"alias_kind":"pith_short_8","alias_value":"NEAREU7U","created_at":"2026-07-05T03:18:07Z"}],"graph_snapshots":[{"event_id":"sha256:3ed0c50dd294a5f9edfc2a7dcce7ba7600dc0b5c499c071a4a1c89eabd6d73eb","target":"graph","created_at":"2026-07-05T03:18:07Z","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/2109.13862/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The success of deep learning for medical imaging tasks, such as classification, is heavily reliant on the availability of large-scale datasets. However, acquiring datasets with large quantities of labeled data is challenging, as labeling is expensive and time-consuming. Semi-supervised learning (SSL) is a growing alternative to fully-supervised learning, but requires unlabeled samples for training. In medical imaging, many datasets lack unlabeled data entirely, so SSL can't be conventionally utilized. We propose 3N-GAN, or 3 Network Generative Adversarial Networks, to perform semi-supervised c","authors_text":"Ayaan Haque, Shafin Haque","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2021-09-22T23:18:59Z","title":"3N-GAN: Semi-Supervised Classification of X-Ray Images with a 3-Player Adversarial Framework"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.13862","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":"sha256:31519391fdec504b897c4e814d7a8ffad8400695f1305ba4b830f0223b86d74c","target":"record","created_at":"2026-07-05T03:18:07Z","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":"4e8da37e52780a9d72c0ee3ca2638cbe9aad173f3742358916f023f5f68a4f11","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2021-09-22T23:18:59Z","title_canon_sha256":"9f625acca0984dab9a9cf6e4af029b21949dc2d2ec33782f7470fb6a78daabf4"},"schema_version":"1.0","source":{"id":"2109.13862","kind":"arxiv","version":1}},"canonical_sha256":"69011253f4d5dec8b570382c62f473594f1dda378065bf9192f408bbb62dcc4d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"69011253f4d5dec8b570382c62f473594f1dda378065bf9192f408bbb62dcc4d","first_computed_at":"2026-07-05T03:18:07.153485Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:18:07.153485Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KvoXA4tcv3yvnc29wnCoYoH7vUrfBWvmW/xTiix4NSjjacoSHmChoBmlXSYGyvHJPMtoZkpi8GwNWKSQEljRAA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:18:07.153905Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.13862","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:31519391fdec504b897c4e814d7a8ffad8400695f1305ba4b830f0223b86d74c","sha256:3ed0c50dd294a5f9edfc2a7dcce7ba7600dc0b5c499c071a4a1c89eabd6d73eb"],"state_sha256":"cdb33325903aa8c9fa6bcf067dcd039e0156137e5ec307fd134efe20ee5e7d87"}