{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:PXEXPQUKDSCDVZUCCYVBJT3EKH","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":"4ddacce60b6a4a2341f988ce1d1b52a1a81952bbd56198004fdacaf9d2b88ce2","cross_cats_sorted":["stat.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-03-21T19:17:26Z","title_canon_sha256":"f70a70ecd147673b86f44a6efa7906cd97cc5b41ec32bf768b1a89833239a4e1"},"schema_version":"1.0","source":{"id":"2203.11300","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.11300","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"arxiv_version","alias_value":"2203.11300v3","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.11300","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"pith_short_12","alias_value":"PXEXPQUKDSCD","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"pith_short_16","alias_value":"PXEXPQUKDSCDVZUC","created_at":"2026-07-05T05:05:03Z"},{"alias_kind":"pith_short_8","alias_value":"PXEXPQUK","created_at":"2026-07-05T05:05:03Z"}],"graph_snapshots":[{"event_id":"sha256:66ff204cf9be43a167020a76842dc74f54c42c05d748876b6942aaa3dafabbd6","target":"graph","created_at":"2026-07-05T05:05:03Z","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/2203.11300/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"M-estimation is a general statistical framework that simplifies estimation. Here, we introduce delicatessen, a Python library that automates the tedious calculations of M-estimation, and supports both built-in user-specified estimating equations. To highlight the utility of delicatessen for quantitative data analysis, we provide several illustrations common to life science research: linear regression robust to outliers, estimation of a dose-response curve, and standardization of results.","authors_text":"Bonnie E Shook-Sa, Jessie K Edwards, Mark Klose, Paul N Zivich, Stephen R Cole","cross_cats":["stat.CO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-03-21T19:17:26Z","title":"Delicatessen: M-Estimation in Python"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.11300","kind":"arxiv","version":3},"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":"sha256:75ba85e5d83a23932f0b2fe0533060ad309a38bd50738d5777a5356224b6e9c3","target":"record","created_at":"2026-07-05T05:05:03Z","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":"4ddacce60b6a4a2341f988ce1d1b52a1a81952bbd56198004fdacaf9d2b88ce2","cross_cats_sorted":["stat.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-03-21T19:17:26Z","title_canon_sha256":"f70a70ecd147673b86f44a6efa7906cd97cc5b41ec32bf768b1a89833239a4e1"},"schema_version":"1.0","source":{"id":"2203.11300","kind":"arxiv","version":3}},"canonical_sha256":"7dc977c28a1c843ae682162a14cf6451e27d939c58676039a73debb426a2ce35","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7dc977c28a1c843ae682162a14cf6451e27d939c58676039a73debb426a2ce35","first_computed_at":"2026-07-05T05:05:03.769471Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:05:03.769471Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8lCkJ2KHjFFxNEIP3yZvBipY6oKOU/595i9/Wz+sPmWqpshuHGdYgga4FUTRyVUpxw3pyIffpPmrFIP0GhuqBw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:05:03.769917Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.11300","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:75ba85e5d83a23932f0b2fe0533060ad309a38bd50738d5777a5356224b6e9c3","sha256:66ff204cf9be43a167020a76842dc74f54c42c05d748876b6942aaa3dafabbd6"],"state_sha256":"ad423433dc4afc2fdd012adc9f5f570b8caab6884ebdaf1fda7b3557c8dcdfdb"}