{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:POPU5IM74PVRRWMA7MP2YNEBST","short_pith_number":"pith:POPU5IM7","canonical_record":{"source":{"id":"2111.08536","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-16T15:06:42Z","cross_cats_sorted":[],"title_canon_sha256":"b76b454b4face8f64e0bf1e4bf4884ad8fdfb691240c5819c897f253dfc7fe9f","abstract_canon_sha256":"58e89981a9ed2824add5d80bd134150b968d20edeb7c315fd46c43d4ae05a997"},"schema_version":"1.0"},"canonical_sha256":"7b9f4ea19fe3eb18d980fb1fac348194dc4b210b3a54f2833bd86540b539bc37","source":{"kind":"arxiv","id":"2111.08536","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.08536","created_at":"2026-07-05T03:48:47Z"},{"alias_kind":"arxiv_version","alias_value":"2111.08536v4","created_at":"2026-07-05T03:48:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.08536","created_at":"2026-07-05T03:48:47Z"},{"alias_kind":"pith_short_12","alias_value":"POPU5IM74PVR","created_at":"2026-07-05T03:48:47Z"},{"alias_kind":"pith_short_16","alias_value":"POPU5IM74PVRRWMA","created_at":"2026-07-05T03:48:47Z"},{"alias_kind":"pith_short_8","alias_value":"POPU5IM7","created_at":"2026-07-05T03:48:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:POPU5IM74PVRRWMA7MP2YNEBST","target":"record","payload":{"canonical_record":{"source":{"id":"2111.08536","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-16T15:06:42Z","cross_cats_sorted":[],"title_canon_sha256":"b76b454b4face8f64e0bf1e4bf4884ad8fdfb691240c5819c897f253dfc7fe9f","abstract_canon_sha256":"58e89981a9ed2824add5d80bd134150b968d20edeb7c315fd46c43d4ae05a997"},"schema_version":"1.0"},"canonical_sha256":"7b9f4ea19fe3eb18d980fb1fac348194dc4b210b3a54f2833bd86540b539bc37","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:48:47.197382Z","signature_b64":"TPTKwwsem3aTC1YXJNy2Tt9Z4urAT5meFQqn1LHMilh/7UYIPvkTf1TegpkcbWJl2+n3ddrRJAwV4ONDO5a1Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7b9f4ea19fe3eb18d980fb1fac348194dc4b210b3a54f2833bd86540b539bc37","last_reissued_at":"2026-07-05T03:48:47.196980Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:48:47.196980Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2111.08536","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:48:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u3kVrYikMQl7bN8igrhO3we3Kk5wKh3Zs30sY94O6oZMpd71m5983JG7LeNxZjl8VnlB/MvDijq5QLQYy8M3Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-24T03:10:17.499341Z"},"content_sha256":"27f14dead1a85b82ead7e5fead5d92a6d7f51375fc61abfb2963f28bb76f28eb","schema_version":"1.0","event_id":"sha256:27f14dead1a85b82ead7e5fead5d92a6d7f51375fc61abfb2963f28bb76f28eb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:POPU5IM74PVRRWMA7MP2YNEBST","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Gunnar R\\\"atsch, Hugo Y\\`eche, Marc Zimmermann, Martin Faltys, Matthias H\\\"user, Rita Kuznetsova, Xinrui Lyu","submitted_at":"2021-11-16T15:06:42Z","abstract_excerpt":"The recent success of machine learning methods applied to time series collected from Intensive Care Units (ICU) exposes the lack of standardized machine learning benchmarks for developing and comparing such methods. While raw datasets, such as MIMIC-IV or eICU, can be freely accessed on Physionet, the choice of tasks and pre-processing is often chosen ad-hoc for each publication, limiting comparability across publications. In this work, we aim to improve this situation by providing a benchmark covering a large spectrum of ICU-related tasks. Using the HiRID dataset, we define multiple clinicall"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.08536","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2111.08536/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:48:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AbIeSknGjF2Civu2h3DmOUWwS/5KS27yw0EKYBwAG9WN9qBbGzgxLwkd/Lz1fPrcd/PS8ILRQPDjeFdREKxaAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-24T03:10:17.500091Z"},"content_sha256":"78331a400741ed16d2a57358a034cf169d4c767a1304954853fd446816310e6e","schema_version":"1.0","event_id":"sha256:78331a400741ed16d2a57358a034cf169d4c767a1304954853fd446816310e6e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/POPU5IM74PVRRWMA7MP2YNEBST/bundle.json","state_url":"https://pith.science/pith/POPU5IM74PVRRWMA7MP2YNEBST/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/POPU5IM74PVRRWMA7MP2YNEBST/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-24T03:10:17Z","links":{"resolver":"https://pith.science/pith/POPU5IM74PVRRWMA7MP2YNEBST","bundle":"https://pith.science/pith/POPU5IM74PVRRWMA7MP2YNEBST/bundle.json","state":"https://pith.science/pith/POPU5IM74PVRRWMA7MP2YNEBST/state.json","well_known_bundle":"https://pith.science/.well-known/pith/POPU5IM74PVRRWMA7MP2YNEBST/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:POPU5IM74PVRRWMA7MP2YNEBST","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":"58e89981a9ed2824add5d80bd134150b968d20edeb7c315fd46c43d4ae05a997","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-16T15:06:42Z","title_canon_sha256":"b76b454b4face8f64e0bf1e4bf4884ad8fdfb691240c5819c897f253dfc7fe9f"},"schema_version":"1.0","source":{"id":"2111.08536","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.08536","created_at":"2026-07-05T03:48:47Z"},{"alias_kind":"arxiv_version","alias_value":"2111.08536v4","created_at":"2026-07-05T03:48:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.08536","created_at":"2026-07-05T03:48:47Z"},{"alias_kind":"pith_short_12","alias_value":"POPU5IM74PVR","created_at":"2026-07-05T03:48:47Z"},{"alias_kind":"pith_short_16","alias_value":"POPU5IM74PVRRWMA","created_at":"2026-07-05T03:48:47Z"},{"alias_kind":"pith_short_8","alias_value":"POPU5IM7","created_at":"2026-07-05T03:48:47Z"}],"graph_snapshots":[{"event_id":"sha256:78331a400741ed16d2a57358a034cf169d4c767a1304954853fd446816310e6e","target":"graph","created_at":"2026-07-05T03:48:47Z","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/2111.08536/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The recent success of machine learning methods applied to time series collected from Intensive Care Units (ICU) exposes the lack of standardized machine learning benchmarks for developing and comparing such methods. While raw datasets, such as MIMIC-IV or eICU, can be freely accessed on Physionet, the choice of tasks and pre-processing is often chosen ad-hoc for each publication, limiting comparability across publications. In this work, we aim to improve this situation by providing a benchmark covering a large spectrum of ICU-related tasks. Using the HiRID dataset, we define multiple clinicall","authors_text":"Gunnar R\\\"atsch, Hugo Y\\`eche, Marc Zimmermann, Martin Faltys, Matthias H\\\"user, Rita Kuznetsova, Xinrui Lyu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-16T15:06:42Z","title":"HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.08536","kind":"arxiv","version":4},"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":"sha256:27f14dead1a85b82ead7e5fead5d92a6d7f51375fc61abfb2963f28bb76f28eb","target":"record","created_at":"2026-07-05T03:48:47Z","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":"58e89981a9ed2824add5d80bd134150b968d20edeb7c315fd46c43d4ae05a997","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-11-16T15:06:42Z","title_canon_sha256":"b76b454b4face8f64e0bf1e4bf4884ad8fdfb691240c5819c897f253dfc7fe9f"},"schema_version":"1.0","source":{"id":"2111.08536","kind":"arxiv","version":4}},"canonical_sha256":"7b9f4ea19fe3eb18d980fb1fac348194dc4b210b3a54f2833bd86540b539bc37","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7b9f4ea19fe3eb18d980fb1fac348194dc4b210b3a54f2833bd86540b539bc37","first_computed_at":"2026-07-05T03:48:47.196980Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:48:47.196980Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TPTKwwsem3aTC1YXJNy2Tt9Z4urAT5meFQqn1LHMilh/7UYIPvkTf1TegpkcbWJl2+n3ddrRJAwV4ONDO5a1Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:48:47.197382Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.08536","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:27f14dead1a85b82ead7e5fead5d92a6d7f51375fc61abfb2963f28bb76f28eb","sha256:78331a400741ed16d2a57358a034cf169d4c767a1304954853fd446816310e6e"],"state_sha256":"0e7dcd3595b3b3a0aaa8c8d3aaddab20c3cf4bd325d3cb2be00652bbab3f2d37"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iwp9JC+4wHPwUIBKz9PZtCGtNy0GihCPGIpHm0BAGYiH9ovyDskAAWaKKQsjcQT0ODKdnrguEjXjxelaltSrDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-24T03:10:17.504811Z","bundle_sha256":"78d79a599cd0eef218774e2c8feb90cfd4e6ee69f551162c3014acb895477100"}}