{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:EXW7UZRCREQP6PQ6WHM26UF2OY","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":"92c2a42e3ca275bd2a0d5f87f0f5aaf13a1c489b229b219e04bcf79fda497d41","cross_cats_sorted":["stat.TH"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"math.ST","submitted_at":"2023-01-31T01:11:18Z","title_canon_sha256":"7c1c844aee973396a9f0c9964343993b6008a4750fbd31773da2d18d912ec21b"},"schema_version":"1.0","source":{"id":"2301.13354","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.13354","created_at":"2026-07-05T05:37:13Z"},{"alias_kind":"arxiv_version","alias_value":"2301.13354v1","created_at":"2026-07-05T05:37:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.13354","created_at":"2026-07-05T05:37:13Z"},{"alias_kind":"pith_short_12","alias_value":"EXW7UZRCREQP","created_at":"2026-07-05T05:37:13Z"},{"alias_kind":"pith_short_16","alias_value":"EXW7UZRCREQP6PQ6","created_at":"2026-07-05T05:37:13Z"},{"alias_kind":"pith_short_8","alias_value":"EXW7UZRC","created_at":"2026-07-05T05:37:13Z"}],"graph_snapshots":[{"event_id":"sha256:1521f3ea8509bc986e715114c748dfb76d8dc7302134f791541fa78c05168410","target":"graph","created_at":"2026-07-05T05:37:13Z","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/2301.13354/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We consider estimation of a functional of the data distribution based on i.i.d. observations. We assume the target function can be defined as the minimizer of the expectation of a loss function over a class of $d$-variate real valued cadlag functions that have finite sectional variation norm. For all $k=0,1,\\ldots$, we define a $k$-th order smoothness class of functions as $d$-variate functions on the unit cube for which each of a sequentially defined $k$-th order Radon-Nikodym derivative w.r.t. Lebesgue measure is cadlag and of bounded variation. For a target function in this $k$-th order smo","authors_text":"Mark van der Laan","cross_cats":["stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"math.ST","submitted_at":"2023-01-31T01:11:18Z","title":"Higher Order Spline Highly Adaptive Lasso Estimators of Functional Parameters: Pointwise Asymptotic Normality and Uniform Convergence Rates"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.13354","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":"sha256:25ab9d5a71385c71827c9d0f688582d2740ebbfbd284ae9d18603d94f357f307","target":"record","created_at":"2026-07-05T05:37:13Z","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":"92c2a42e3ca275bd2a0d5f87f0f5aaf13a1c489b229b219e04bcf79fda497d41","cross_cats_sorted":["stat.TH"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"math.ST","submitted_at":"2023-01-31T01:11:18Z","title_canon_sha256":"7c1c844aee973396a9f0c9964343993b6008a4750fbd31773da2d18d912ec21b"},"schema_version":"1.0","source":{"id":"2301.13354","kind":"arxiv","version":1}},"canonical_sha256":"25edfa66228920ff3e1eb1d9af50ba760269c179a8681734367108c44e6879dd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"25edfa66228920ff3e1eb1d9af50ba760269c179a8681734367108c44e6879dd","first_computed_at":"2026-07-05T05:37:13.846471Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:37:13.846471Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"S9YCzGLnSeRuzUx2MW83dcpzYAarDy5BTkZdKFNDMNLRyyGkCZNyzY1AYK2Hm1qT2IyoaAverKr2u4bOyZQVBA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:37:13.847215Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.13354","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:25ab9d5a71385c71827c9d0f688582d2740ebbfbd284ae9d18603d94f357f307","sha256:1521f3ea8509bc986e715114c748dfb76d8dc7302134f791541fa78c05168410"],"state_sha256":"12b09d15435c3907b665600af217e28bd5b75ee76508d635ae103d15250e72e4"}