{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:BRXGSBGRJKA6VR4GM5B34VKHS6","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":"8353c7abe5d934ef79abbbc6bf9ec472e2aa844fafdcc77bc9b80edc70be2477","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-06-01T01:41:16Z","title_canon_sha256":"2c2432a650e47ab41ddb2ca998f34035e6260c5197d0dd37668f4d3d25ef9368"},"schema_version":"1.0","source":{"id":"2606.01539","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.01539","created_at":"2026-06-02T02:04:35Z"},{"alias_kind":"arxiv_version","alias_value":"2606.01539v1","created_at":"2026-06-02T02:04:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.01539","created_at":"2026-06-02T02:04:35Z"},{"alias_kind":"pith_short_12","alias_value":"BRXGSBGRJKA6","created_at":"2026-06-02T02:04:35Z"},{"alias_kind":"pith_short_16","alias_value":"BRXGSBGRJKA6VR4G","created_at":"2026-06-02T02:04:35Z"},{"alias_kind":"pith_short_8","alias_value":"BRXGSBGR","created_at":"2026-06-02T02:04:35Z"}],"graph_snapshots":[{"event_id":"sha256:32655d36f9520d5c3423aaf0476ec9d2d06d17d7fb296d866d48aa2b6cdc51d0","target":"graph","created_at":"2026-06-02T02:04:35Z","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/2606.01539/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Estimating the causal effect of time-varying treatments on survival outcomes in large observational studies is computationally demanding, particularly when outcomes are rare. While g-formula-based methods such as the iterative conditional expectation (ICE) estimator provide a principled framework for longitudinal causal inference, they become computationally expensive, especially when bootstrap-based variance estimation is required. In addition, outcome rarity at each time point induces severe class imbalance, leading to instability and convergence issues in logistic regression and related mod","authors_text":"Avijit Mitra, Hong Yu, Kun Chen, Xiaohui Yin, Ying Zhou","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-06-01T01:41:16Z","title":"Scalable Counterfactual Risk Estimation for Rare Events in Longitudinal Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.01539","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:c48c0d4f8dfef2d2cd3bbd500b1feb753de38f3d476d6f4fffbed2d2da9397dc","target":"record","created_at":"2026-06-02T02:04:35Z","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":"8353c7abe5d934ef79abbbc6bf9ec472e2aa844fafdcc77bc9b80edc70be2477","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-06-01T01:41:16Z","title_canon_sha256":"2c2432a650e47ab41ddb2ca998f34035e6260c5197d0dd37668f4d3d25ef9368"},"schema_version":"1.0","source":{"id":"2606.01539","kind":"arxiv","version":1}},"canonical_sha256":"0c6e6904d14a81eac7866743be554797be5077a69723c5f3f6a676101fd35597","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0c6e6904d14a81eac7866743be554797be5077a69723c5f3f6a676101fd35597","first_computed_at":"2026-06-02T02:04:35.866466Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T02:04:35.866466Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hxdZdgCHaUKtCBUNF+bsdaRcp/9hZtCHfUVmyZBl1k49zFZ9vPh1EC8GoSrEAMq2jIkAkM4Y/XpcPVVqnYs2Cg==","signature_status":"signed_v1","signed_at":"2026-06-02T02:04:35.866838Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.01539","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c48c0d4f8dfef2d2cd3bbd500b1feb753de38f3d476d6f4fffbed2d2da9397dc","sha256:32655d36f9520d5c3423aaf0476ec9d2d06d17d7fb296d866d48aa2b6cdc51d0"],"state_sha256":"42c39827cd199075c2829ca70f43ab67d1706e4e7c93510dc3b771f1f0d9af31"}