{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:WBQIZI5OO2C5SMVOXOQRBGE6EH","short_pith_number":"pith:WBQIZI5O","canonical_record":{"source":{"id":"1602.06896","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-22T19:11:28Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"c4025885f8ed7a97968a299417feb0a8a7c2a6565bbbd5c9d9a8a93f70ef805a","abstract_canon_sha256":"c7cc1ab89c16df1eeb7c5936d2e27170ef6a24f40c302fe7168e43f76c2b9b04"},"schema_version":"1.0"},"canonical_sha256":"b0608ca3ae7685d932aebba110989e21e9bd0d997829f0d51675b3f3cc6bfc72","source":{"kind":"arxiv","id":"1602.06896","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.06896","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"arxiv_version","alias_value":"1602.06896v1","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.06896","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"pith_short_12","alias_value":"WBQIZI5OO2C5","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_16","alias_value":"WBQIZI5OO2C5SMVO","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_8","alias_value":"WBQIZI5O","created_at":"2026-05-18T12:30:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:WBQIZI5OO2C5SMVOXOQRBGE6EH","target":"record","payload":{"canonical_record":{"source":{"id":"1602.06896","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-22T19:11:28Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"c4025885f8ed7a97968a299417feb0a8a7c2a6565bbbd5c9d9a8a93f70ef805a","abstract_canon_sha256":"c7cc1ab89c16df1eeb7c5936d2e27170ef6a24f40c302fe7168e43f76c2b9b04"},"schema_version":"1.0"},"canonical_sha256":"b0608ca3ae7685d932aebba110989e21e9bd0d997829f0d51675b3f3cc6bfc72","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:34:00.101488Z","signature_b64":"24Rdk9R/g/TsZuoVjCKdNd01OxANP/J+jClqB8f4OJe5q1Hw98KrcM//WkiXjwLuF97QemxWLQjsuQvDfiz6BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b0608ca3ae7685d932aebba110989e21e9bd0d997829f0d51675b3f3cc6bfc72","last_reissued_at":"2026-05-18T00:34:00.100885Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:34:00.100885Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1602.06896","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":"2026-05-18T00:34:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3Rki6MwtWvxB9uQSYHJOXOfjPXdqaBIePwspJa4LcKGRelS+faYvE996SARkaaGgnd3GZzBmTrqNlPq1fgUFCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T05:39:18.433908Z"},"content_sha256":"5c548aa90cdccf27c844b9690dfb697a24dadc225ee70b94d205fbd82bfa3d52","schema_version":"1.0","event_id":"sha256:5c548aa90cdccf27c844b9690dfb697a24dadc225ee70b94d205fbd82bfa3d52"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:WBQIZI5OO2C5SMVOXOQRBGE6EH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sharp detection in PCA under correlations: all eigenvalues matter","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Edgar Dobriban","submitted_at":"2016-02-22T19:11:28Z","abstract_excerpt":"Principal component analysis (PCA) is a widely used method for dimension reduction. In high dimensional data, the \"signal\" eigenvalues corresponding to weak principal components (PCs) do not necessarily separate from the bulk of the \"noise\" eigenvalues. Therefore, popular tests based on the largest eigenvalue have little power to detect weak PCs. In the special case of the spiked model, certain tests asymptotically equivalent to linear spectral statistics (LSS)---averaging effects over all eigenvalues---were recently shown to achieve some power.\n  We consider a nonparametric, non-Gaussian gene"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.06896","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":"2026-05-18T00:34:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EQnYMBsYNgIC/XU8BLFX2TFlA7klfp7pRelupBCxAmYCYwBnlmhfYDAqsoHvxy7hIgSD08scd3VCjapHa4/BAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T05:39:18.434289Z"},"content_sha256":"115a2314612f7366999d6d883f59d23c0d41519049da004f9b6d278b655f2fa8","schema_version":"1.0","event_id":"sha256:115a2314612f7366999d6d883f59d23c0d41519049da004f9b6d278b655f2fa8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WBQIZI5OO2C5SMVOXOQRBGE6EH/bundle.json","state_url":"https://pith.science/pith/WBQIZI5OO2C5SMVOXOQRBGE6EH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WBQIZI5OO2C5SMVOXOQRBGE6EH/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":"2026-06-07T05:39:18Z","links":{"resolver":"https://pith.science/pith/WBQIZI5OO2C5SMVOXOQRBGE6EH","bundle":"https://pith.science/pith/WBQIZI5OO2C5SMVOXOQRBGE6EH/bundle.json","state":"https://pith.science/pith/WBQIZI5OO2C5SMVOXOQRBGE6EH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WBQIZI5OO2C5SMVOXOQRBGE6EH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:WBQIZI5OO2C5SMVOXOQRBGE6EH","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":"c7cc1ab89c16df1eeb7c5936d2e27170ef6a24f40c302fe7168e43f76c2b9b04","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-22T19:11:28Z","title_canon_sha256":"c4025885f8ed7a97968a299417feb0a8a7c2a6565bbbd5c9d9a8a93f70ef805a"},"schema_version":"1.0","source":{"id":"1602.06896","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.06896","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"arxiv_version","alias_value":"1602.06896v1","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.06896","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"pith_short_12","alias_value":"WBQIZI5OO2C5","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_16","alias_value":"WBQIZI5OO2C5SMVO","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_8","alias_value":"WBQIZI5O","created_at":"2026-05-18T12:30:48Z"}],"graph_snapshots":[{"event_id":"sha256:115a2314612f7366999d6d883f59d23c0d41519049da004f9b6d278b655f2fa8","target":"graph","created_at":"2026-05-18T00:34:00Z","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":"Principal component analysis (PCA) is a widely used method for dimension reduction. In high dimensional data, the \"signal\" eigenvalues corresponding to weak principal components (PCs) do not necessarily separate from the bulk of the \"noise\" eigenvalues. Therefore, popular tests based on the largest eigenvalue have little power to detect weak PCs. In the special case of the spiked model, certain tests asymptotically equivalent to linear spectral statistics (LSS)---averaging effects over all eigenvalues---were recently shown to achieve some power.\n  We consider a nonparametric, non-Gaussian gene","authors_text":"Edgar Dobriban","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-22T19:11:28Z","title":"Sharp detection in PCA under correlations: all eigenvalues matter"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.06896","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":"sha256:5c548aa90cdccf27c844b9690dfb697a24dadc225ee70b94d205fbd82bfa3d52","target":"record","created_at":"2026-05-18T00:34:00Z","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":"c7cc1ab89c16df1eeb7c5936d2e27170ef6a24f40c302fe7168e43f76c2b9b04","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-22T19:11:28Z","title_canon_sha256":"c4025885f8ed7a97968a299417feb0a8a7c2a6565bbbd5c9d9a8a93f70ef805a"},"schema_version":"1.0","source":{"id":"1602.06896","kind":"arxiv","version":1}},"canonical_sha256":"b0608ca3ae7685d932aebba110989e21e9bd0d997829f0d51675b3f3cc6bfc72","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b0608ca3ae7685d932aebba110989e21e9bd0d997829f0d51675b3f3cc6bfc72","first_computed_at":"2026-05-18T00:34:00.100885Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:34:00.100885Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"24Rdk9R/g/TsZuoVjCKdNd01OxANP/J+jClqB8f4OJe5q1Hw98KrcM//WkiXjwLuF97QemxWLQjsuQvDfiz6BA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:34:00.101488Z","signed_message":"canonical_sha256_bytes"},"source_id":"1602.06896","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5c548aa90cdccf27c844b9690dfb697a24dadc225ee70b94d205fbd82bfa3d52","sha256:115a2314612f7366999d6d883f59d23c0d41519049da004f9b6d278b655f2fa8"],"state_sha256":"55aad36320f5ded215680f76eaac8c099e8a5c3f41199e07f45d2590b425c4fc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TLkGLc8VmJUF7nLhEt0weOfL8okWH+jf686oN4ooa2CEfivP+9IXQWNXBzInztiQ0cPSWUEE9kWdhwtnG4gWCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T05:39:18.436338Z","bundle_sha256":"8d2f04d3613773a8824e839190638ab318d0831ab241604b143c3f5299e283ff"}}