{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:2NK23QWABNF2NM6FID2D2EPFEV","short_pith_number":"pith:2NK23QWA","canonical_record":{"source":{"id":"1905.07923","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-05-20T07:36:26Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"866547021f1f7bf196cf1cbb137ce2b60f2db37d039766f08a1056ffebf9cdad","abstract_canon_sha256":"940daa50bf3971ac8980731465d1d6333bf3e1c51b2fb7ea6dd90debb403524e"},"schema_version":"1.0"},"canonical_sha256":"d355adc2c00b4ba6b3c540f43d11e5254b22b7a4c8151549a8f0056a4d897d8e","source":{"kind":"arxiv","id":"1905.07923","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.07923","created_at":"2026-05-17T23:45:48Z"},{"alias_kind":"arxiv_version","alias_value":"1905.07923v1","created_at":"2026-05-17T23:45:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.07923","created_at":"2026-05-17T23:45:48Z"},{"alias_kind":"pith_short_12","alias_value":"2NK23QWABNF2","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"2NK23QWABNF2NM6F","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"2NK23QWA","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:2NK23QWABNF2NM6FID2D2EPFEV","target":"record","payload":{"canonical_record":{"source":{"id":"1905.07923","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-05-20T07:36:26Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"866547021f1f7bf196cf1cbb137ce2b60f2db37d039766f08a1056ffebf9cdad","abstract_canon_sha256":"940daa50bf3971ac8980731465d1d6333bf3e1c51b2fb7ea6dd90debb403524e"},"schema_version":"1.0"},"canonical_sha256":"d355adc2c00b4ba6b3c540f43d11e5254b22b7a4c8151549a8f0056a4d897d8e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:45:48.075742Z","signature_b64":"b6zl3KPabk8Pfm0/+10UgC+NF11I7nytavtGOrp8BbxIhcCzRxVcBLmfvtCy4Q2QZ2DhAWJiucDS5QulvIxwBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d355adc2c00b4ba6b3c540f43d11e5254b22b7a4c8151549a8f0056a4d897d8e","last_reissued_at":"2026-05-17T23:45:48.075075Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:45:48.075075Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.07923","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":"2026-05-17T23:45:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aRuqzktvoDxx30x9LKsfdul9l3vIWhjev9r8nsO9GDGowAnIy5xL7K10MTV7Rojk6tVH2NrnDn9lnW3K3msMDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T18:44:58.678354Z"},"content_sha256":"37e7b1b436ca67e62555adb2c50dc0346b3442c0d4c5c0e18091a5b9f65d8c1c","schema_version":"1.0","event_id":"sha256:37e7b1b436ca67e62555adb2c50dc0346b3442c0d4c5c0e18091a5b9f65d8c1c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:2NK23QWABNF2NM6FID2D2EPFEV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Transmitter Classification With Supervised Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE"],"primary_cat":"eess.SP","authors_text":"Cyrille Morin (MARACAS), Jakob Hoydis, Jean-Marie Gorce (MARACAS), Leonardo Cardoso (MARACAS), Thibaud Vial","submitted_at":"2019-05-20T07:36:26Z","abstract_excerpt":"Hardware imperfections in RF transmitters introduce features that can be used to identify a specific transmitter amongst others. Supervised deep learning has shown good performance in this task but using datasets not applicable to real world situations where topologies evolve over time. To remedy this, the work rests on a series of datasets gathered in the Future Internet of Things / Cognitive Radio Testbed [4] (FIT/CorteXlab) to train a convolutional neural network (CNN), where focus has been given to reduce channel bias that has plagued previous works and constrained them to a constant envir"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.07923","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":"2026-05-17T23:45:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5AOUep5Gu0niNQQuZeChnoOuPWLaNTRMyJfZVsM6v2FtEhbC7enm1zA7Qat6qwEuTg6YAJsb2LBtlQnQB3sGAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T18:44:58.679355Z"},"content_sha256":"da36aa7aba251f65c5ba740f16de0bbbeef7b63b9ee1e94b2d4e1d0872f79ae4","schema_version":"1.0","event_id":"sha256:da36aa7aba251f65c5ba740f16de0bbbeef7b63b9ee1e94b2d4e1d0872f79ae4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2NK23QWABNF2NM6FID2D2EPFEV/bundle.json","state_url":"https://pith.science/pith/2NK23QWABNF2NM6FID2D2EPFEV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2NK23QWABNF2NM6FID2D2EPFEV/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":"2026-08-03T18:44:58Z","links":{"resolver":"https://pith.science/pith/2NK23QWABNF2NM6FID2D2EPFEV","bundle":"https://pith.science/pith/2NK23QWABNF2NM6FID2D2EPFEV/bundle.json","state":"https://pith.science/pith/2NK23QWABNF2NM6FID2D2EPFEV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2NK23QWABNF2NM6FID2D2EPFEV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:2NK23QWABNF2NM6FID2D2EPFEV","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":"940daa50bf3971ac8980731465d1d6333bf3e1c51b2fb7ea6dd90debb403524e","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-05-20T07:36:26Z","title_canon_sha256":"866547021f1f7bf196cf1cbb137ce2b60f2db37d039766f08a1056ffebf9cdad"},"schema_version":"1.0","source":{"id":"1905.07923","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.07923","created_at":"2026-05-17T23:45:48Z"},{"alias_kind":"arxiv_version","alias_value":"1905.07923v1","created_at":"2026-05-17T23:45:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.07923","created_at":"2026-05-17T23:45:48Z"},{"alias_kind":"pith_short_12","alias_value":"2NK23QWABNF2","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"2NK23QWABNF2NM6F","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"2NK23QWA","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:da36aa7aba251f65c5ba740f16de0bbbeef7b63b9ee1e94b2d4e1d0872f79ae4","target":"graph","created_at":"2026-05-17T23:45:48Z","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":"Hardware imperfections in RF transmitters introduce features that can be used to identify a specific transmitter amongst others. Supervised deep learning has shown good performance in this task but using datasets not applicable to real world situations where topologies evolve over time. To remedy this, the work rests on a series of datasets gathered in the Future Internet of Things / Cognitive Radio Testbed [4] (FIT/CorteXlab) to train a convolutional neural network (CNN), where focus has been given to reduce channel bias that has plagued previous works and constrained them to a constant envir","authors_text":"Cyrille Morin (MARACAS), Jakob Hoydis, Jean-Marie Gorce (MARACAS), Leonardo Cardoso (MARACAS), Thibaud Vial","cross_cats":["cs.LG","cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-05-20T07:36:26Z","title":"Transmitter Classification With Supervised Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.07923","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":"sha256:37e7b1b436ca67e62555adb2c50dc0346b3442c0d4c5c0e18091a5b9f65d8c1c","target":"record","created_at":"2026-05-17T23:45:48Z","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":"940daa50bf3971ac8980731465d1d6333bf3e1c51b2fb7ea6dd90debb403524e","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-05-20T07:36:26Z","title_canon_sha256":"866547021f1f7bf196cf1cbb137ce2b60f2db37d039766f08a1056ffebf9cdad"},"schema_version":"1.0","source":{"id":"1905.07923","kind":"arxiv","version":1}},"canonical_sha256":"d355adc2c00b4ba6b3c540f43d11e5254b22b7a4c8151549a8f0056a4d897d8e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d355adc2c00b4ba6b3c540f43d11e5254b22b7a4c8151549a8f0056a4d897d8e","first_computed_at":"2026-05-17T23:45:48.075075Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:45:48.075075Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"b6zl3KPabk8Pfm0/+10UgC+NF11I7nytavtGOrp8BbxIhcCzRxVcBLmfvtCy4Q2QZ2DhAWJiucDS5QulvIxwBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:45:48.075742Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.07923","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:37e7b1b436ca67e62555adb2c50dc0346b3442c0d4c5c0e18091a5b9f65d8c1c","sha256:da36aa7aba251f65c5ba740f16de0bbbeef7b63b9ee1e94b2d4e1d0872f79ae4"],"state_sha256":"94abb33679c39c82fa71af7d560126c30d87cb00bccb8839b53d09b2b0b98b23"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/sCJ0C7vYXCtlM2Vx7kyBxU4PNYSJYdE6YWEYhTRK8FMpfXIw5QzXIMmXjIUpGNvPIwCcLDjw6iGjQAeYanmAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T18:44:58.684631Z","bundle_sha256":"cff18808a2b71e107279d28ce93613d3957e3ba42001cff0d05e47aafe547eaa"}}