{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:6SZXJ7IVL7MMX5UXODRGFMWF2N","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":"049355409aa4f677d514fa2a66026b27e6e33598dc297fcd57b4dd8e41642596","cross_cats_sorted":["cs.MS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-06T02:40:45Z","title_canon_sha256":"636db7eb2ff545aed94e5f843a87889b2a5055c2a1417728645c00505b8daef6"},"schema_version":"1.0","source":{"id":"2508.04740","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.04740","created_at":"2026-07-05T11:50:00Z"},{"alias_kind":"arxiv_version","alias_value":"2508.04740v1","created_at":"2026-07-05T11:50:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.04740","created_at":"2026-07-05T11:50:00Z"},{"alias_kind":"pith_short_12","alias_value":"6SZXJ7IVL7MM","created_at":"2026-07-05T11:50:00Z"},{"alias_kind":"pith_short_16","alias_value":"6SZXJ7IVL7MMX5UX","created_at":"2026-07-05T11:50:00Z"},{"alias_kind":"pith_short_8","alias_value":"6SZXJ7IV","created_at":"2026-07-05T11:50:00Z"}],"graph_snapshots":[{"event_id":"sha256:c33272375068b49acfddbeb2384229325be3743165775f5324872e65b00dc7ff","target":"graph","created_at":"2026-07-05T11:50:00Z","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/2508.04740/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Incomplete data is a persistent challenge in real-world datasets, often governed by complex and unobservable missing mechanisms. Simulating missingness has become a standard approach for understanding its impact on learning and analysis. However, existing tools are fragmented, mechanism-limited, and typically focus only on numerical variables, overlooking the heterogeneous nature of real-world tabular data. We present MissMecha, an open-source Python toolkit for simulating, visualizing, and evaluating missing data under MCAR, MAR, and MNAR assumptions. MissMecha supports both numerical and cat","authors_text":"Mohamed Reda Bouadjenek, Sunil Aryal, Youran Zhou","cross_cats":["cs.MS"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-06T02:40:45Z","title":"MissMecha: An All-in-One Python Package for Studying Missing Data Mechanisms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.04740","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:fa363080c09eedfddcd09dee5903b25eeeefe58518d9a4d2bc7b84603bbe1a3c","target":"record","created_at":"2026-07-05T11:50:00Z","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":"049355409aa4f677d514fa2a66026b27e6e33598dc297fcd57b4dd8e41642596","cross_cats_sorted":["cs.MS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-06T02:40:45Z","title_canon_sha256":"636db7eb2ff545aed94e5f843a87889b2a5055c2a1417728645c00505b8daef6"},"schema_version":"1.0","source":{"id":"2508.04740","kind":"arxiv","version":1}},"canonical_sha256":"f4b374fd155fd8cbf69770e262b2c5d36c8c01cdfb4557fcbfa10a44170eacb2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f4b374fd155fd8cbf69770e262b2c5d36c8c01cdfb4557fcbfa10a44170eacb2","first_computed_at":"2026-07-05T11:50:00.938651Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:50:00.938651Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UjYXZkkmbZgfK20eR7VL47gKFz84Sg9x45wvzt9VWiDtK3UWiM64K/Mm25Wlt7e3nh0RNVXg2hJHul8dFXJ1Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:50:00.939080Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.04740","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fa363080c09eedfddcd09dee5903b25eeeefe58518d9a4d2bc7b84603bbe1a3c","sha256:c33272375068b49acfddbeb2384229325be3743165775f5324872e65b00dc7ff"],"state_sha256":"d2eb0c29c19bb144d164a6f8bfc3c12a7cea5b113e45bdb2e4f2d0269f302064"}