{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:UGW3PTHBBVJ4TRJKT4XS37O3PO","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":"a75c83f39725e66290eda3e360d38a8990cbe3741f16e1b005de2717e736bd2f","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-01-14T01:12:00Z","title_canon_sha256":"9882cddcde626cd9ced072844d5d1c39914c46ed068558a99eae14665660d496"},"schema_version":"1.0","source":{"id":"1501.03227","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1501.03227","created_at":"2026-07-05T02:14:07Z"},{"alias_kind":"arxiv_version","alias_value":"1501.03227v3","created_at":"2026-07-05T02:14:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1501.03227","created_at":"2026-07-05T02:14:07Z"},{"alias_kind":"pith_short_12","alias_value":"UGW3PTHBBVJ4","created_at":"2026-07-05T02:14:07Z"},{"alias_kind":"pith_short_16","alias_value":"UGW3PTHBBVJ4TRJK","created_at":"2026-07-05T02:14:07Z"},{"alias_kind":"pith_short_8","alias_value":"UGW3PTHB","created_at":"2026-07-05T02:14:07Z"}],"graph_snapshots":[{"event_id":"sha256:6ce837fbb9ccf795d7db4fb29a1896812f0dbe2b14d1d3353e2269ee935b2c43","target":"graph","created_at":"2026-07-05T02:14:07Z","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/1501.03227/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Riemannian geometry has been applied to Brain Computer Interface (BCI) for brain signals classification yielding promising results. Studying electroencephalographic (EEG) signals from their associated covariance matrices allows a mitigation of common sources of variability (electronic, electrical, biological) by constructing a representation which is invariant to these perturbations. While working in Euclidean space with covariance matrices is known to be error-prone, one might take advantage of algorithmic advances in information geometry and matrix manifold to implement methods for Symmetric","authors_text":"Emmanuel K. Kalunga, Quentin Barthelemy, Sylvain Chevallier","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-01-14T01:12:00Z","title":"Using Riemannian geometry for SSVEP-based Brain Computer Interface"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1501.03227","kind":"arxiv","version":3},"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:f0d1bb3004a1dbcdeb3daee0e8666948d90ac745af05b1729f8debfe724776ed","target":"record","created_at":"2026-07-05T02:14:07Z","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":"a75c83f39725e66290eda3e360d38a8990cbe3741f16e1b005de2717e736bd2f","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-01-14T01:12:00Z","title_canon_sha256":"9882cddcde626cd9ced072844d5d1c39914c46ed068558a99eae14665660d496"},"schema_version":"1.0","source":{"id":"1501.03227","kind":"arxiv","version":3}},"canonical_sha256":"a1adb7cce10d53c9c52a9f2f2dfddb7ba5b7b6466a3ba1744b1f5a28687b3adc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a1adb7cce10d53c9c52a9f2f2dfddb7ba5b7b6466a3ba1744b1f5a28687b3adc","first_computed_at":"2026-07-05T02:14:07.483328Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:14:07.483328Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aXOyEVXd8zHZmBMnV8hT3vq69wi20c4rrYoAC6NIYSyF+VbCWDWV7TBDE+zC2SwLytCRDwcLO0u18aj6oV+MBg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:14:07.483953Z","signed_message":"canonical_sha256_bytes"},"source_id":"1501.03227","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f0d1bb3004a1dbcdeb3daee0e8666948d90ac745af05b1729f8debfe724776ed","sha256:6ce837fbb9ccf795d7db4fb29a1896812f0dbe2b14d1d3353e2269ee935b2c43"],"state_sha256":"39ea24dc665b23ccdb3f2914bf0d82aa6c04effa3ff82caeb2b9dcd0bcc099de"}