{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:FBG3TKZC2BTMW3534URD6SOIGD","short_pith_number":"pith:FBG3TKZC","schema_version":"1.0","canonical_sha256":"284db9ab22d066cb6fbbe5223f49c830ea0b761529e64d60bbe7cba1ed632f09","source":{"kind":"arxiv","id":"1710.06056","version":1},"attestation_state":"computed","paper":{"title":"Asymptotically Optimal Sequential Design for Rank Aggregation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Xiaoou Li, Xi Chen, Yunxiao Chen","submitted_at":"2017-10-17T02:15:55Z","abstract_excerpt":"A sequential design problem for rank aggregation is commonly encountered in psychology, politics, marketing, sports, etc. In this problem, a decision maker is responsible for ranking $K$ items by sequentially collecting pairwise noisy comparison from judges. The decision maker needs to choose a pair of items for comparison in each step, decide when to stop data collection, and make a final decision after stopping, based on a sequential flow of information. Due to the complex ranking structure, existing sequential analysis methods are not suitable.\n  In this paper, we formulate the problem unde"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1710.06056","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-10-17T02:15:55Z","cross_cats_sorted":[],"title_canon_sha256":"037e94a3520e1ae75b80394fa36f8fdfb7ad5cab12a0277983995bf0b32948fe","abstract_canon_sha256":"35ba64457942f926496e213afd6d017c5749002483d84a042a3a201525bcc3c7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:32:37.919553Z","signature_b64":"4KaKyb+5QJUeCXb78LjNETQynaByDxa1sFFiNvXpzfIBBpxJqNa29PUWppi3i7EQIM9OUA8xfdz0IddEM+1rCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"284db9ab22d066cb6fbbe5223f49c830ea0b761529e64d60bbe7cba1ed632f09","last_reissued_at":"2026-05-18T00:32:37.918840Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:32:37.918840Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Asymptotically Optimal Sequential Design for Rank Aggregation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Xiaoou Li, Xi Chen, Yunxiao Chen","submitted_at":"2017-10-17T02:15:55Z","abstract_excerpt":"A sequential design problem for rank aggregation is commonly encountered in psychology, politics, marketing, sports, etc. In this problem, a decision maker is responsible for ranking $K$ items by sequentially collecting pairwise noisy comparison from judges. The decision maker needs to choose a pair of items for comparison in each step, decide when to stop data collection, and make a final decision after stopping, based on a sequential flow of information. Due to the complex ranking structure, existing sequential analysis methods are not suitable.\n  In this paper, we formulate the problem unde"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.06056","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1710.06056","created_at":"2026-05-18T00:32:37.918965+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.06056v1","created_at":"2026-05-18T00:32:37.918965+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.06056","created_at":"2026-05-18T00:32:37.918965+00:00"},{"alias_kind":"pith_short_12","alias_value":"FBG3TKZC2BTM","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_16","alias_value":"FBG3TKZC2BTMW353","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_8","alias_value":"FBG3TKZC","created_at":"2026-05-18T12:31:15.632608+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/FBG3TKZC2BTMW3534URD6SOIGD","json":"https://pith.science/pith/FBG3TKZC2BTMW3534URD6SOIGD.json","graph_json":"https://pith.science/api/pith-number/FBG3TKZC2BTMW3534URD6SOIGD/graph.json","events_json":"https://pith.science/api/pith-number/FBG3TKZC2BTMW3534URD6SOIGD/events.json","paper":"https://pith.science/paper/FBG3TKZC"},"agent_actions":{"view_html":"https://pith.science/pith/FBG3TKZC2BTMW3534URD6SOIGD","download_json":"https://pith.science/pith/FBG3TKZC2BTMW3534URD6SOIGD.json","view_paper":"https://pith.science/paper/FBG3TKZC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.06056&json=true","fetch_graph":"https://pith.science/api/pith-number/FBG3TKZC2BTMW3534URD6SOIGD/graph.json","fetch_events":"https://pith.science/api/pith-number/FBG3TKZC2BTMW3534URD6SOIGD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FBG3TKZC2BTMW3534URD6SOIGD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FBG3TKZC2BTMW3534URD6SOIGD/action/storage_attestation","attest_author":"https://pith.science/pith/FBG3TKZC2BTMW3534URD6SOIGD/action/author_attestation","sign_citation":"https://pith.science/pith/FBG3TKZC2BTMW3534URD6SOIGD/action/citation_signature","submit_replication":"https://pith.science/pith/FBG3TKZC2BTMW3534URD6SOIGD/action/replication_record"}},"created_at":"2026-05-18T00:32:37.918965+00:00","updated_at":"2026-05-18T00:32:37.918965+00:00"}