{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:M3A7OCZITNLA7HWI3LK6ZROCQQ","short_pith_number":"pith:M3A7OCZI","canonical_record":{"source":{"id":"2408.03816","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T14:52:06Z","cross_cats_sorted":[],"title_canon_sha256":"ee7bf10b96cdcd998de07b4fee4b96fe1d534efe78a69b76f6aca47bfb5ada25","abstract_canon_sha256":"d5cd5b286b19d65925799ec714c2103207df241d90c7ff5c0134c90257e498ac"},"schema_version":"1.0"},"canonical_sha256":"66c1f70b289b560f9ec8dad5ecc5c2842f400c1a895c6e746700312c3a10b90a","source":{"kind":"arxiv","id":"2408.03816","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.03816","created_at":"2026-07-05T08:59:11Z"},{"alias_kind":"arxiv_version","alias_value":"2408.03816v2","created_at":"2026-07-05T08:59:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.03816","created_at":"2026-07-05T08:59:11Z"},{"alias_kind":"pith_short_12","alias_value":"M3A7OCZITNLA","created_at":"2026-07-05T08:59:11Z"},{"alias_kind":"pith_short_16","alias_value":"M3A7OCZITNLA7HWI","created_at":"2026-07-05T08:59:11Z"},{"alias_kind":"pith_short_8","alias_value":"M3A7OCZI","created_at":"2026-07-05T08:59:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:M3A7OCZITNLA7HWI3LK6ZROCQQ","target":"record","payload":{"canonical_record":{"source":{"id":"2408.03816","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T14:52:06Z","cross_cats_sorted":[],"title_canon_sha256":"ee7bf10b96cdcd998de07b4fee4b96fe1d534efe78a69b76f6aca47bfb5ada25","abstract_canon_sha256":"d5cd5b286b19d65925799ec714c2103207df241d90c7ff5c0134c90257e498ac"},"schema_version":"1.0"},"canonical_sha256":"66c1f70b289b560f9ec8dad5ecc5c2842f400c1a895c6e746700312c3a10b90a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:59:11.373014Z","signature_b64":"elm+YTFRuDSHCVmoHCiS6nbNcXWZz9jcni/ld38LT2H0EGchowFA25zM14K945hLffNQGs7Bmsg+RVXX0o4pBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"66c1f70b289b560f9ec8dad5ecc5c2842f400c1a895c6e746700312c3a10b90a","last_reissued_at":"2026-07-05T08:59:11.372478Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:59:11.372478Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.03816","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:59:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0h3i/z9cK/PxiFwJysczmDB5A8RM+QjzCB8M099biiFodUZ9cr/M3WLRI4rg25hT9PUte8DlkQosFFwNM446AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T18:32:02.694186Z"},"content_sha256":"fba281b9085399154772db2693e2a89c50b0dcae3638296a6ef970f36cd06036","schema_version":"1.0","event_id":"sha256:fba281b9085399154772db2693e2a89c50b0dcae3638296a6ef970f36cd06036"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:M3A7OCZITNLA7HWI3LK6ZROCQQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Early Prediction of Causes (not Effects) in Healthcare by Long-Term Clinical Time Series Forecasting","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Marius Fracarolli, Michael Hagmann, Michael Staniek, Stefan Riezler","submitted_at":"2024-08-07T14:52:06Z","abstract_excerpt":"Machine learning for early syndrome diagnosis aims to solve the intricate task of predicting a ground truth label that most often is the outcome (effect) of a medical consensus definition applied to observed clinical measurements (causes), given clinical measurements observed several hours before. Instead of focusing on the prediction of the future effect, we propose to directly predict the causes via time series forecasting (TSF) of clinical variables and determine the effect by applying the gold standard consensus definition to the forecasted values. This method has the invaluable advantage "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.03816","kind":"arxiv","version":2},"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/2408.03816/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":"2026-07-05T08:59:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/YpPu0LPrkNXhaKIcHy1bh/iSq+CTS+svLg8zDifDHhfiAg3e5QYESSXQWeJQUc2SK8oxerkJbBYlrxw8kyVDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T18:32:02.694802Z"},"content_sha256":"13aca6e580027041cb1382d0a21158e609780e75e532e83afaf9573582dbdfa7","schema_version":"1.0","event_id":"sha256:13aca6e580027041cb1382d0a21158e609780e75e532e83afaf9573582dbdfa7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M3A7OCZITNLA7HWI3LK6ZROCQQ/bundle.json","state_url":"https://pith.science/pith/M3A7OCZITNLA7HWI3LK6ZROCQQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M3A7OCZITNLA7HWI3LK6ZROCQQ/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":"2026-08-07T18:32:02Z","links":{"resolver":"https://pith.science/pith/M3A7OCZITNLA7HWI3LK6ZROCQQ","bundle":"https://pith.science/pith/M3A7OCZITNLA7HWI3LK6ZROCQQ/bundle.json","state":"https://pith.science/pith/M3A7OCZITNLA7HWI3LK6ZROCQQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M3A7OCZITNLA7HWI3LK6ZROCQQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:M3A7OCZITNLA7HWI3LK6ZROCQQ","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":"d5cd5b286b19d65925799ec714c2103207df241d90c7ff5c0134c90257e498ac","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T14:52:06Z","title_canon_sha256":"ee7bf10b96cdcd998de07b4fee4b96fe1d534efe78a69b76f6aca47bfb5ada25"},"schema_version":"1.0","source":{"id":"2408.03816","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.03816","created_at":"2026-07-05T08:59:11Z"},{"alias_kind":"arxiv_version","alias_value":"2408.03816v2","created_at":"2026-07-05T08:59:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.03816","created_at":"2026-07-05T08:59:11Z"},{"alias_kind":"pith_short_12","alias_value":"M3A7OCZITNLA","created_at":"2026-07-05T08:59:11Z"},{"alias_kind":"pith_short_16","alias_value":"M3A7OCZITNLA7HWI","created_at":"2026-07-05T08:59:11Z"},{"alias_kind":"pith_short_8","alias_value":"M3A7OCZI","created_at":"2026-07-05T08:59:11Z"}],"graph_snapshots":[{"event_id":"sha256:13aca6e580027041cb1382d0a21158e609780e75e532e83afaf9573582dbdfa7","target":"graph","created_at":"2026-07-05T08:59:11Z","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/2408.03816/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning for early syndrome diagnosis aims to solve the intricate task of predicting a ground truth label that most often is the outcome (effect) of a medical consensus definition applied to observed clinical measurements (causes), given clinical measurements observed several hours before. Instead of focusing on the prediction of the future effect, we propose to directly predict the causes via time series forecasting (TSF) of clinical variables and determine the effect by applying the gold standard consensus definition to the forecasted values. This method has the invaluable advantage ","authors_text":"Marius Fracarolli, Michael Hagmann, Michael Staniek, Stefan Riezler","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T14:52:06Z","title":"Early Prediction of Causes (not Effects) in Healthcare by Long-Term Clinical Time Series Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.03816","kind":"arxiv","version":2},"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:fba281b9085399154772db2693e2a89c50b0dcae3638296a6ef970f36cd06036","target":"record","created_at":"2026-07-05T08:59:11Z","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":"d5cd5b286b19d65925799ec714c2103207df241d90c7ff5c0134c90257e498ac","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-07T14:52:06Z","title_canon_sha256":"ee7bf10b96cdcd998de07b4fee4b96fe1d534efe78a69b76f6aca47bfb5ada25"},"schema_version":"1.0","source":{"id":"2408.03816","kind":"arxiv","version":2}},"canonical_sha256":"66c1f70b289b560f9ec8dad5ecc5c2842f400c1a895c6e746700312c3a10b90a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"66c1f70b289b560f9ec8dad5ecc5c2842f400c1a895c6e746700312c3a10b90a","first_computed_at":"2026-07-05T08:59:11.372478Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:59:11.372478Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"elm+YTFRuDSHCVmoHCiS6nbNcXWZz9jcni/ld38LT2H0EGchowFA25zM14K945hLffNQGs7Bmsg+RVXX0o4pBA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:59:11.373014Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.03816","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fba281b9085399154772db2693e2a89c50b0dcae3638296a6ef970f36cd06036","sha256:13aca6e580027041cb1382d0a21158e609780e75e532e83afaf9573582dbdfa7"],"state_sha256":"7e3f42721915279b3c04ee960d2f77604f1efa8eec70cf09a379997c3ae9574a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oyDwXxCy9Wccz+eRVW76GYcNDM10ZRG7tFUEIUNGzuIW302h/unA1VdvV68YOtjngmUwb3wEUMYJjvJZPQlGDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T18:32:02.704875Z","bundle_sha256":"7892a6c92730b719d5e06b41ae4e83c163090eff04fff356658fd380e4be8b38"}}