{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:2IUO6IGNTAYIXLULMLCR6SZADA","short_pith_number":"pith:2IUO6IGN","canonical_record":{"source":{"id":"1710.00633","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-10-02T13:36:29Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"c4d2cd7d8638bb6e0c920f12c3b08c7f1c3b7f78a4cb0624996c9bec728e1e9a","abstract_canon_sha256":"072162f0df1674f24d92d3a55924aa55297257470820c66974371a5344cb6be0"},"schema_version":"1.0"},"canonical_sha256":"d228ef20cd98308bae8b62c51f4b20182e3d6d682913a910ef541bb87cffb82e","source":{"kind":"arxiv","id":"1710.00633","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.00633","created_at":"2026-05-18T00:33:54Z"},{"alias_kind":"arxiv_version","alias_value":"1710.00633v1","created_at":"2026-05-18T00:33:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.00633","created_at":"2026-05-18T00:33:54Z"},{"alias_kind":"pith_short_12","alias_value":"2IUO6IGNTAYI","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"2IUO6IGNTAYIXLUL","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"2IUO6IGN","created_at":"2026-05-18T12:30:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:2IUO6IGNTAYIXLULMLCR6SZADA","target":"record","payload":{"canonical_record":{"source":{"id":"1710.00633","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-10-02T13:36:29Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"c4d2cd7d8638bb6e0c920f12c3b08c7f1c3b7f78a4cb0624996c9bec728e1e9a","abstract_canon_sha256":"072162f0df1674f24d92d3a55924aa55297257470820c66974371a5344cb6be0"},"schema_version":"1.0"},"canonical_sha256":"d228ef20cd98308bae8b62c51f4b20182e3d6d682913a910ef541bb87cffb82e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:33:54.197887Z","signature_b64":"eiwHATNTPV9CrgAoPUrlFu7DKwyXuFpRPkBOqQtg/5ysjhPf0YOvDP4C2S2O9uRKCYTKLBs6k4NdnXttUpAxAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d228ef20cd98308bae8b62c51f4b20182e3d6d682913a910ef541bb87cffb82e","last_reissued_at":"2026-05-18T00:33:54.197235Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:33:54.197235Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1710.00633","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":"2026-05-18T00:33:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9NgZK45o86WSQAy9UtwCkATLjBk7hmfX+WUKRkEfaOuqF0A8grrfbcyl8ownFoCHMEnJonOyMfLOqNQS4Se1BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-02T14:16:10.066421Z"},"content_sha256":"f5e4e66ffad7d2e2a6ff0d1a890319adde0fe2f0fcb41aac1636981efa80a0d4","schema_version":"1.0","event_id":"sha256:f5e4e66ffad7d2e2a6ff0d1a890319adde0fe2f0fcb41aac1636981efa80a0d4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:2IUO6IGNTAYIXLULMLCR6SZADA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Convolutional Neural Networks for Interpretable Analysis of EEG Sleep Stage Scoring","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.CV","authors_text":"Albert Vilamala, Kristoffer H. Madsen, Lars K. Hansen","submitted_at":"2017-10-02T13:36:29Z","abstract_excerpt":"Sleep studies are important for diagnosing sleep disorders such as insomnia, narcolepsy or sleep apnea. They rely on manual scoring of sleep stages from raw polisomnography signals, which is a tedious visual task requiring the workload of highly trained professionals. Consequently, research efforts to purse for an automatic stage scoring based on machine learning techniques have been carried out over the last years. In this work, we resort to multitaper spectral analysis to create visually interpretable images of sleep patterns from EEG signals as inputs to a deep convolutional network trained"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.00633","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":"2026-05-18T00:33:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B7OIv0HR40TroOPTedsJrILKeandI5XoKBj+IE2y/CcwuFQPcOPQHKt+tvkw7r4IZebOEsVDsYOCVCP95BBqDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-02T14:16:10.066767Z"},"content_sha256":"9a89633e7a293f879df708c56b4436e61d948223d84d66a0c1e791af88de58d0","schema_version":"1.0","event_id":"sha256:9a89633e7a293f879df708c56b4436e61d948223d84d66a0c1e791af88de58d0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2IUO6IGNTAYIXLULMLCR6SZADA/bundle.json","state_url":"https://pith.science/pith/2IUO6IGNTAYIXLULMLCR6SZADA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2IUO6IGNTAYIXLULMLCR6SZADA/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":"2026-07-02T14:16:10Z","links":{"resolver":"https://pith.science/pith/2IUO6IGNTAYIXLULMLCR6SZADA","bundle":"https://pith.science/pith/2IUO6IGNTAYIXLULMLCR6SZADA/bundle.json","state":"https://pith.science/pith/2IUO6IGNTAYIXLULMLCR6SZADA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2IUO6IGNTAYIXLULMLCR6SZADA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:2IUO6IGNTAYIXLULMLCR6SZADA","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":"072162f0df1674f24d92d3a55924aa55297257470820c66974371a5344cb6be0","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-10-02T13:36:29Z","title_canon_sha256":"c4d2cd7d8638bb6e0c920f12c3b08c7f1c3b7f78a4cb0624996c9bec728e1e9a"},"schema_version":"1.0","source":{"id":"1710.00633","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.00633","created_at":"2026-05-18T00:33:54Z"},{"alias_kind":"arxiv_version","alias_value":"1710.00633v1","created_at":"2026-05-18T00:33:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.00633","created_at":"2026-05-18T00:33:54Z"},{"alias_kind":"pith_short_12","alias_value":"2IUO6IGNTAYI","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"2IUO6IGNTAYIXLUL","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"2IUO6IGN","created_at":"2026-05-18T12:30:55Z"}],"graph_snapshots":[{"event_id":"sha256:9a89633e7a293f879df708c56b4436e61d948223d84d66a0c1e791af88de58d0","target":"graph","created_at":"2026-05-18T00:33:54Z","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":"Sleep studies are important for diagnosing sleep disorders such as insomnia, narcolepsy or sleep apnea. They rely on manual scoring of sleep stages from raw polisomnography signals, which is a tedious visual task requiring the workload of highly trained professionals. Consequently, research efforts to purse for an automatic stage scoring based on machine learning techniques have been carried out over the last years. In this work, we resort to multitaper spectral analysis to create visually interpretable images of sleep patterns from EEG signals as inputs to a deep convolutional network trained","authors_text":"Albert Vilamala, Kristoffer H. Madsen, Lars K. Hansen","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-10-02T13:36:29Z","title":"Deep Convolutional Neural Networks for Interpretable Analysis of EEG Sleep Stage Scoring"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.00633","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:f5e4e66ffad7d2e2a6ff0d1a890319adde0fe2f0fcb41aac1636981efa80a0d4","target":"record","created_at":"2026-05-18T00:33:54Z","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":"072162f0df1674f24d92d3a55924aa55297257470820c66974371a5344cb6be0","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-10-02T13:36:29Z","title_canon_sha256":"c4d2cd7d8638bb6e0c920f12c3b08c7f1c3b7f78a4cb0624996c9bec728e1e9a"},"schema_version":"1.0","source":{"id":"1710.00633","kind":"arxiv","version":1}},"canonical_sha256":"d228ef20cd98308bae8b62c51f4b20182e3d6d682913a910ef541bb87cffb82e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d228ef20cd98308bae8b62c51f4b20182e3d6d682913a910ef541bb87cffb82e","first_computed_at":"2026-05-18T00:33:54.197235Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:33:54.197235Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eiwHATNTPV9CrgAoPUrlFu7DKwyXuFpRPkBOqQtg/5ysjhPf0YOvDP4C2S2O9uRKCYTKLBs6k4NdnXttUpAxAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:33:54.197887Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.00633","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f5e4e66ffad7d2e2a6ff0d1a890319adde0fe2f0fcb41aac1636981efa80a0d4","sha256:9a89633e7a293f879df708c56b4436e61d948223d84d66a0c1e791af88de58d0"],"state_sha256":"17c27ace7ff2abd469f2342b860bae0aa91dc05be8e618d2ff6d87d644574e35"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"euNYE8PdSzJUNtWHRLhFD7R8x3XeC6xTDfW/dmNySulM6Wm5Mdtorw48L/NW7XC8wA1s67l6xtEoabiW9j0QCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-02T14:16:10.068838Z","bundle_sha256":"244cc59c8d5fb4363ab91e176e0c4771a1324c68dcba59bb9e420ec3faa6be1b"}}