{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:EPICXDIQQ5VGUYS765O7LZRETC","short_pith_number":"pith:EPICXDIQ","canonical_record":{"source":{"id":"1802.10238","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-28T02:39:02Z","cross_cats_sorted":["cs.AI","stat.AP","stat.ML"],"title_canon_sha256":"02955d7d59209aef439a5938b877a75345f5c9d5fe1d3fa7365311c98cbe00b8","abstract_canon_sha256":"4598dacb3d6fb128101855d2d1f6b17e40c7de6acb2a0d7ccde26403911e2505"},"schema_version":"1.0"},"canonical_sha256":"23d02b8d10876a6a625ff75df5e6249894a2bdafa346e7b2294cfe380deb02a4","source":{"kind":"arxiv","id":"1802.10238","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10238","created_at":"2026-05-17T23:54:07Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10238v4","created_at":"2026-05-17T23:54:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10238","created_at":"2026-05-17T23:54:07Z"},{"alias_kind":"pith_short_12","alias_value":"EPICXDIQQ5VG","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"EPICXDIQQ5VGUYS7","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"EPICXDIQ","created_at":"2026-05-18T12:32:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:EPICXDIQQ5VGUYS765O7LZRETC","target":"record","payload":{"canonical_record":{"source":{"id":"1802.10238","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-28T02:39:02Z","cross_cats_sorted":["cs.AI","stat.AP","stat.ML"],"title_canon_sha256":"02955d7d59209aef439a5938b877a75345f5c9d5fe1d3fa7365311c98cbe00b8","abstract_canon_sha256":"4598dacb3d6fb128101855d2d1f6b17e40c7de6acb2a0d7ccde26403911e2505"},"schema_version":"1.0"},"canonical_sha256":"23d02b8d10876a6a625ff75df5e6249894a2bdafa346e7b2294cfe380deb02a4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:54:07.429309Z","signature_b64":"X61CyMNxkDUl2bGuOG3oLDngFnOV6lI0bcmyTKP4zJ9xMG/kmfVAUT/8A4U9+WmqDOrjHsGTYHGJ+12CVH4+Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"23d02b8d10876a6a625ff75df5e6249894a2bdafa346e7b2294cfe380deb02a4","last_reissued_at":"2026-05-17T23:54:07.428794Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:54:07.428794Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.10238","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":"2026-05-17T23:54:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YfZygIKtay2CZpQ6LYDltPB1nJMBpgxDnCpMZ7Q/E18MTfcf2l6oxThe9RoUiVtYCyyOFfncRlNRId0MM4BzAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T10:25:52.500996Z"},"content_sha256":"7329562172f81a261264db67e5d01d5088d622b7f268f04a7fd59c2fc8ea1408","schema_version":"1.0","event_id":"sha256:7329562172f81a261264db67e5d01d5088d622b7f268f04a7fd59c2fc8ea1408"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:EPICXDIQQ5VGUYS765O7LZRETC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.AP","stat.ML"],"primary_cat":"cs.LG","authors_text":"Azra Bihorac, Benjamin Shickel, Lasith Adhikari, Parisa Rashidi, Tezcan Ozrazgat-Baslanti, Tyler J. Loftus","submitted_at":"2018-02-28T02:39:02Z","abstract_excerpt":"Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static variable thresholds. These methods do not capitalize on the emerging availability of streaming electronic health record data or capture time-sensitive individual physiological patterns, a critical task in the intensive care unit. We propose a novel acuity score framework (DeepSOFA) that leverages temporal measurements and interpretable deep learning models to assess illness severity at any point during an ICU stay. W"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10238","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":""},"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":"2026-05-17T23:54:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1lufxFuWk3XeyWW0jgMXPrcVXO8IU6P4Dpe7FDkvSOWAjt3CeB4ofIsSEiJvOmRPyJolKaGTrsON37ixKA5XBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T10:25:52.501373Z"},"content_sha256":"563c5d03241e7d6a5cb6f5a7a7f4aa11be85abbe67a9c07c21eae2a9ccc817d8","schema_version":"1.0","event_id":"sha256:563c5d03241e7d6a5cb6f5a7a7f4aa11be85abbe67a9c07c21eae2a9ccc817d8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EPICXDIQQ5VGUYS765O7LZRETC/bundle.json","state_url":"https://pith.science/pith/EPICXDIQQ5VGUYS765O7LZRETC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EPICXDIQQ5VGUYS765O7LZRETC/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":"2026-05-21T10:25:52Z","links":{"resolver":"https://pith.science/pith/EPICXDIQQ5VGUYS765O7LZRETC","bundle":"https://pith.science/pith/EPICXDIQQ5VGUYS765O7LZRETC/bundle.json","state":"https://pith.science/pith/EPICXDIQQ5VGUYS765O7LZRETC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EPICXDIQQ5VGUYS765O7LZRETC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:EPICXDIQQ5VGUYS765O7LZRETC","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":"4598dacb3d6fb128101855d2d1f6b17e40c7de6acb2a0d7ccde26403911e2505","cross_cats_sorted":["cs.AI","stat.AP","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-28T02:39:02Z","title_canon_sha256":"02955d7d59209aef439a5938b877a75345f5c9d5fe1d3fa7365311c98cbe00b8"},"schema_version":"1.0","source":{"id":"1802.10238","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10238","created_at":"2026-05-17T23:54:07Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10238v4","created_at":"2026-05-17T23:54:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10238","created_at":"2026-05-17T23:54:07Z"},{"alias_kind":"pith_short_12","alias_value":"EPICXDIQQ5VG","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"EPICXDIQQ5VGUYS7","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"EPICXDIQ","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:563c5d03241e7d6a5cb6f5a7a7f4aa11be85abbe67a9c07c21eae2a9ccc817d8","target":"graph","created_at":"2026-05-17T23:54:07Z","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"},"paper":{"abstract_excerpt":"Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static variable thresholds. These methods do not capitalize on the emerging availability of streaming electronic health record data or capture time-sensitive individual physiological patterns, a critical task in the intensive care unit. We propose a novel acuity score framework (DeepSOFA) that leverages temporal measurements and interpretable deep learning models to assess illness severity at any point during an ICU stay. W","authors_text":"Azra Bihorac, Benjamin Shickel, Lasith Adhikari, Parisa Rashidi, Tezcan Ozrazgat-Baslanti, Tyler J. Loftus","cross_cats":["cs.AI","stat.AP","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-28T02:39:02Z","title":"DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10238","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":"sha256:7329562172f81a261264db67e5d01d5088d622b7f268f04a7fd59c2fc8ea1408","target":"record","created_at":"2026-05-17T23:54:07Z","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":"4598dacb3d6fb128101855d2d1f6b17e40c7de6acb2a0d7ccde26403911e2505","cross_cats_sorted":["cs.AI","stat.AP","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-02-28T02:39:02Z","title_canon_sha256":"02955d7d59209aef439a5938b877a75345f5c9d5fe1d3fa7365311c98cbe00b8"},"schema_version":"1.0","source":{"id":"1802.10238","kind":"arxiv","version":4}},"canonical_sha256":"23d02b8d10876a6a625ff75df5e6249894a2bdafa346e7b2294cfe380deb02a4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"23d02b8d10876a6a625ff75df5e6249894a2bdafa346e7b2294cfe380deb02a4","first_computed_at":"2026-05-17T23:54:07.428794Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:54:07.428794Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"X61CyMNxkDUl2bGuOG3oLDngFnOV6lI0bcmyTKP4zJ9xMG/kmfVAUT/8A4U9+WmqDOrjHsGTYHGJ+12CVH4+Aw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:54:07.429309Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.10238","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7329562172f81a261264db67e5d01d5088d622b7f268f04a7fd59c2fc8ea1408","sha256:563c5d03241e7d6a5cb6f5a7a7f4aa11be85abbe67a9c07c21eae2a9ccc817d8"],"state_sha256":"f7a5f3594f1c0cb5d691b920f0df8f5b9118532111cedd49331b37d3b73f189a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oo0PCFyEAxhSXcKWlI+rsR7BfwgrYAyZOzDaiDDsRu7sNLfUNIQkp06GUzS4H0hreS+51DnLJJrky5sLwQ7vAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-21T10:25:52.503640Z","bundle_sha256":"bcfe9d2d6e08e66b06a9d002f5f33cb4857a150637a5e54aafcdbee91b14b872"}}