{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:EGK2E22N6LDIWDYUY6VEXSH4MU","short_pith_number":"pith:EGK2E22N","canonical_record":{"source":{"id":"1402.4539","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-02-19T01:27:43Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6af327fd9ece061b4a4317b4bc71bcb141acf028538a6a43cdc6331c9e58bc8f","abstract_canon_sha256":"6dd9a4ca957cba9e22d0500bd13422f28c57e548eca64ce8f878da9af86404d8"},"schema_version":"1.0"},"canonical_sha256":"2195a26b4df2c68b0f14c7aa4bc8fc651b2f418610b1edfbfcb0a369fd0f9b94","source":{"kind":"arxiv","id":"1402.4539","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1402.4539","created_at":"2026-05-18T01:19:35Z"},{"alias_kind":"arxiv_version","alias_value":"1402.4539v1","created_at":"2026-05-18T01:19:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1402.4539","created_at":"2026-05-18T01:19:35Z"},{"alias_kind":"pith_short_12","alias_value":"EGK2E22N6LDI","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_16","alias_value":"EGK2E22N6LDIWDYU","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_8","alias_value":"EGK2E22N","created_at":"2026-05-18T12:28:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:EGK2E22N6LDIWDYUY6VEXSH4MU","target":"record","payload":{"canonical_record":{"source":{"id":"1402.4539","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-02-19T01:27:43Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6af327fd9ece061b4a4317b4bc71bcb141acf028538a6a43cdc6331c9e58bc8f","abstract_canon_sha256":"6dd9a4ca957cba9e22d0500bd13422f28c57e548eca64ce8f878da9af86404d8"},"schema_version":"1.0"},"canonical_sha256":"2195a26b4df2c68b0f14c7aa4bc8fc651b2f418610b1edfbfcb0a369fd0f9b94","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:19:35.490928Z","signature_b64":"XHtH4VavyIE5wYF1XRTGlYw4dH+KoLbJICfL3A8DZYW+ECH0NkmB4PZMgWgZSnVk/zeWNQbguvk46U9P4+04DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2195a26b4df2c68b0f14c7aa4bc8fc651b2f418610b1edfbfcb0a369fd0f9b94","last_reissued_at":"2026-05-18T01:19:35.490251Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:19:35.490251Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1402.4539","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":"2026-05-18T01:19:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dIZ5nI4wcn2rZEGXaM8H6A04+b1VHQ3jXi/ydwHKHIooX8P+eHu7l87FzL5x6/GtRVnZYYb2RhyR9yzXwOSHAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T04:05:35.754935Z"},"content_sha256":"68df0a17936283930d1a79066fdb1f545873eaaa951638d3c5fd7473a690cae6","schema_version":"1.0","event_id":"sha256:68df0a17936283930d1a79066fdb1f545873eaaa951638d3c5fd7473a690cae6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:EGK2E22N6LDIWDYUY6VEXSH4MU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Statistical Approach to Set Classification by Feature Selection with Applications to Classification of Histopathology Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"stat.ME","authors_text":"Sungkyu Jung, Xingye Qiao","submitted_at":"2014-02-19T01:27:43Z","abstract_excerpt":"Set classification problems arise when classification tasks are based on sets of observations as opposed to individual observations. In set classification, a classification rule is trained with $N$ sets of observations, where each set is labeled with class information, and the prediction of a class label is performed also with a set of observations. Data sets for set classification appear, for example, in diagnostics of disease based on multiple cell nucleus images from a single tissue. Relevant statistical models for set classification are introduced, which motivate a set classification frame"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1402.4539","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":"2026-05-18T01:19:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eTTyBEabrnbsXk3YTU+5p/fmCprJUUNLS6cEReMyab06rp4mp8cMWn/4CcX9+gydDo6t/rsAijGaa+aZ8K+aBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T04:05:35.755293Z"},"content_sha256":"68ef2a935b97a3fde0fd345e9e6a3e981f91f75dda54299376c3ca5f360e383d","schema_version":"1.0","event_id":"sha256:68ef2a935b97a3fde0fd345e9e6a3e981f91f75dda54299376c3ca5f360e383d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EGK2E22N6LDIWDYUY6VEXSH4MU/bundle.json","state_url":"https://pith.science/pith/EGK2E22N6LDIWDYUY6VEXSH4MU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EGK2E22N6LDIWDYUY6VEXSH4MU/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":"2026-05-28T04:05:35Z","links":{"resolver":"https://pith.science/pith/EGK2E22N6LDIWDYUY6VEXSH4MU","bundle":"https://pith.science/pith/EGK2E22N6LDIWDYUY6VEXSH4MU/bundle.json","state":"https://pith.science/pith/EGK2E22N6LDIWDYUY6VEXSH4MU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EGK2E22N6LDIWDYUY6VEXSH4MU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:EGK2E22N6LDIWDYUY6VEXSH4MU","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":"6dd9a4ca957cba9e22d0500bd13422f28c57e548eca64ce8f878da9af86404d8","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-02-19T01:27:43Z","title_canon_sha256":"6af327fd9ece061b4a4317b4bc71bcb141acf028538a6a43cdc6331c9e58bc8f"},"schema_version":"1.0","source":{"id":"1402.4539","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1402.4539","created_at":"2026-05-18T01:19:35Z"},{"alias_kind":"arxiv_version","alias_value":"1402.4539v1","created_at":"2026-05-18T01:19:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1402.4539","created_at":"2026-05-18T01:19:35Z"},{"alias_kind":"pith_short_12","alias_value":"EGK2E22N6LDI","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_16","alias_value":"EGK2E22N6LDIWDYU","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_8","alias_value":"EGK2E22N","created_at":"2026-05-18T12:28:25Z"}],"graph_snapshots":[{"event_id":"sha256:68ef2a935b97a3fde0fd345e9e6a3e981f91f75dda54299376c3ca5f360e383d","target":"graph","created_at":"2026-05-18T01:19:35Z","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":"Set classification problems arise when classification tasks are based on sets of observations as opposed to individual observations. In set classification, a classification rule is trained with $N$ sets of observations, where each set is labeled with class information, and the prediction of a class label is performed also with a set of observations. Data sets for set classification appear, for example, in diagnostics of disease based on multiple cell nucleus images from a single tissue. Relevant statistical models for set classification are introduced, which motivate a set classification frame","authors_text":"Sungkyu Jung, Xingye Qiao","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-02-19T01:27:43Z","title":"A Statistical Approach to Set Classification by Feature Selection with Applications to Classification of Histopathology Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1402.4539","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":"sha256:68df0a17936283930d1a79066fdb1f545873eaaa951638d3c5fd7473a690cae6","target":"record","created_at":"2026-05-18T01:19:35Z","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":"6dd9a4ca957cba9e22d0500bd13422f28c57e548eca64ce8f878da9af86404d8","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-02-19T01:27:43Z","title_canon_sha256":"6af327fd9ece061b4a4317b4bc71bcb141acf028538a6a43cdc6331c9e58bc8f"},"schema_version":"1.0","source":{"id":"1402.4539","kind":"arxiv","version":1}},"canonical_sha256":"2195a26b4df2c68b0f14c7aa4bc8fc651b2f418610b1edfbfcb0a369fd0f9b94","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2195a26b4df2c68b0f14c7aa4bc8fc651b2f418610b1edfbfcb0a369fd0f9b94","first_computed_at":"2026-05-18T01:19:35.490251Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:19:35.490251Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XHtH4VavyIE5wYF1XRTGlYw4dH+KoLbJICfL3A8DZYW+ECH0NkmB4PZMgWgZSnVk/zeWNQbguvk46U9P4+04DQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:19:35.490928Z","signed_message":"canonical_sha256_bytes"},"source_id":"1402.4539","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:68df0a17936283930d1a79066fdb1f545873eaaa951638d3c5fd7473a690cae6","sha256:68ef2a935b97a3fde0fd345e9e6a3e981f91f75dda54299376c3ca5f360e383d"],"state_sha256":"8b939f4f01d348c929ea2ef58031ce2dabc90f52d762f4dfa1023af15db9ee0b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5Z4UhAJMRxSkyjaQzDnv81vqT3b6TE3kKQp/aT7udcTpA1ESXi4YBg8FsbK1VWaCUXiD5/BIfk5hnUhN5m65DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T04:05:35.757369Z","bundle_sha256":"c58f2e0a14c5e978f0878e22d8c2b181dade1bb5cea61d02ef412d44ac423f21"}}