{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:EBOFUFZCICCDGLXYOJKSJ5RCWU","short_pith_number":"pith:EBOFUFZC","schema_version":"1.0","canonical_sha256":"205c5a17224084332ef8725524f622b5175090109fe3c9e8e14b5f57172b52f8","source":{"kind":"arxiv","id":"1403.4054","version":1},"attestation_state":"computed","paper":{"title":"A general decision framework for structuring computation using Data Directional Scaling to process massive similarity matrices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Daniel John Lawson, Niall M Adams","submitted_at":"2014-03-17T10:22:16Z","abstract_excerpt":"As datasets grow it becomes infeasible to process them completely with a desired model. For giant datasets, we frame the order in which computation is performed as a decision problem. The order is designed so that partial computations are of value and early stopping yields useful results. Our approach comprises two related tools: a decision framework to choose the order to perform computations, and an emulation framework to enable estimation of the unevaluated computations. The approach is applied to the problem of computing similarity matrices, for which the cost of computation grows quadrati"},"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":"1403.4054","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2014-03-17T10:22:16Z","cross_cats_sorted":[],"title_canon_sha256":"d37952c72340b3b3c1f416e92989d81ba4202100f7c79aba35802ba85fbba102","abstract_canon_sha256":"0fe4ab1b73f05114802a4b30345dd443d18d47b3d4e3351575f4aa510a095cde"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:56:12.239670Z","signature_b64":"j2GqG/1SsiejoyQckzAq1jotxd7UQTHjfcKG8zaOyFPNuad7Xp0i03n/qUn+VBL65Y3DjR8mQ4dANFReALpKCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"205c5a17224084332ef8725524f622b5175090109fe3c9e8e14b5f57172b52f8","last_reissued_at":"2026-05-18T02:56:12.239302Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:56:12.239302Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A general decision framework for structuring computation using Data Directional Scaling to process massive similarity matrices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Daniel John Lawson, Niall M Adams","submitted_at":"2014-03-17T10:22:16Z","abstract_excerpt":"As datasets grow it becomes infeasible to process them completely with a desired model. For giant datasets, we frame the order in which computation is performed as a decision problem. The order is designed so that partial computations are of value and early stopping yields useful results. Our approach comprises two related tools: a decision framework to choose the order to perform computations, and an emulation framework to enable estimation of the unevaluated computations. The approach is applied to the problem of computing similarity matrices, for which the cost of computation grows quadrati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1403.4054","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":"1403.4054","created_at":"2026-05-18T02:56:12.239368+00:00"},{"alias_kind":"arxiv_version","alias_value":"1403.4054v1","created_at":"2026-05-18T02:56:12.239368+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1403.4054","created_at":"2026-05-18T02:56:12.239368+00:00"},{"alias_kind":"pith_short_12","alias_value":"EBOFUFZCICCD","created_at":"2026-05-18T12:28:25.294606+00:00"},{"alias_kind":"pith_short_16","alias_value":"EBOFUFZCICCDGLXY","created_at":"2026-05-18T12:28:25.294606+00:00"},{"alias_kind":"pith_short_8","alias_value":"EBOFUFZC","created_at":"2026-05-18T12:28:25.294606+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/EBOFUFZCICCDGLXYOJKSJ5RCWU","json":"https://pith.science/pith/EBOFUFZCICCDGLXYOJKSJ5RCWU.json","graph_json":"https://pith.science/api/pith-number/EBOFUFZCICCDGLXYOJKSJ5RCWU/graph.json","events_json":"https://pith.science/api/pith-number/EBOFUFZCICCDGLXYOJKSJ5RCWU/events.json","paper":"https://pith.science/paper/EBOFUFZC"},"agent_actions":{"view_html":"https://pith.science/pith/EBOFUFZCICCDGLXYOJKSJ5RCWU","download_json":"https://pith.science/pith/EBOFUFZCICCDGLXYOJKSJ5RCWU.json","view_paper":"https://pith.science/paper/EBOFUFZC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1403.4054&json=true","fetch_graph":"https://pith.science/api/pith-number/EBOFUFZCICCDGLXYOJKSJ5RCWU/graph.json","fetch_events":"https://pith.science/api/pith-number/EBOFUFZCICCDGLXYOJKSJ5RCWU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EBOFUFZCICCDGLXYOJKSJ5RCWU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EBOFUFZCICCDGLXYOJKSJ5RCWU/action/storage_attestation","attest_author":"https://pith.science/pith/EBOFUFZCICCDGLXYOJKSJ5RCWU/action/author_attestation","sign_citation":"https://pith.science/pith/EBOFUFZCICCDGLXYOJKSJ5RCWU/action/citation_signature","submit_replication":"https://pith.science/pith/EBOFUFZCICCDGLXYOJKSJ5RCWU/action/replication_record"}},"created_at":"2026-05-18T02:56:12.239368+00:00","updated_at":"2026-05-18T02:56:12.239368+00:00"}