{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:THVJNQHRVIG7UN4S3DWWP5NBO7","short_pith_number":"pith:THVJNQHR","canonical_record":{"source":{"id":"1801.03058","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-01-09T17:51:12Z","cross_cats_sorted":[],"title_canon_sha256":"c8e8fa4987af8f5d1329c73f7b89acd159de61b3a366ecb0db42e1a222911ddb","abstract_canon_sha256":"ac34dfc3e6cea98b8194025a8433e011c651196d8c90df30a7b18a738090a7c3"},"schema_version":"1.0"},"canonical_sha256":"99ea96c0f1aa0dfa3792d8ed67f5a177ef8f30d07d56b3b9e95d2a938d630f71","source":{"kind":"arxiv","id":"1801.03058","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.03058","created_at":"2026-05-18T00:10:46Z"},{"alias_kind":"arxiv_version","alias_value":"1801.03058v2","created_at":"2026-05-18T00:10:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.03058","created_at":"2026-05-18T00:10:46Z"},{"alias_kind":"pith_short_12","alias_value":"THVJNQHRVIG7","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"THVJNQHRVIG7UN4S","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"THVJNQHR","created_at":"2026-05-18T12:32:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:THVJNQHRVIG7UN4S3DWWP5NBO7","target":"record","payload":{"canonical_record":{"source":{"id":"1801.03058","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-01-09T17:51:12Z","cross_cats_sorted":[],"title_canon_sha256":"c8e8fa4987af8f5d1329c73f7b89acd159de61b3a366ecb0db42e1a222911ddb","abstract_canon_sha256":"ac34dfc3e6cea98b8194025a8433e011c651196d8c90df30a7b18a738090a7c3"},"schema_version":"1.0"},"canonical_sha256":"99ea96c0f1aa0dfa3792d8ed67f5a177ef8f30d07d56b3b9e95d2a938d630f71","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:10:46.962552Z","signature_b64":"VMBG4tzlEoPGHIOjEaqIsCNHGj84aQU0BqCX0USbizxKSiK20/4wWQ3FIOt5Mqi/Ki+l+idBL3dXP+kPSspYBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"99ea96c0f1aa0dfa3792d8ed67f5a177ef8f30d07d56b3b9e95d2a938d630f71","last_reissued_at":"2026-05-18T00:10:46.961732Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:10:46.961732Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1801.03058","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":"2026-05-18T00:10:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W74NI6moT4igsxeNk8fSGmBk9MigS7DtnTER4zFQpYPOxXKnU9Ljed84by+NeJyHxa0HeJUJ8CnO5T8v//CGDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T01:17:08.752237Z"},"content_sha256":"b866a83b78d3b94abfbb3ba991e25b51681b2d42da02105b957f78edff5109d2","schema_version":"1.0","event_id":"sha256:b866a83b78d3b94abfbb3ba991e25b51681b2d42da02105b957f78edff5109d2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:THVJNQHRVIG7UN4S3DWWP5NBO7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Abstract: Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Daniel Chang, Daniel L. Rubin, Douglas J. Wood, Imon Banerjee, Michael Francis Gensheimer, Solomon Henry","submitted_at":"2018-01-09T17:51:12Z","abstract_excerpt":"We propose a deep learning model - Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) for estimating short-term life expectancy (3 months) of the patients by analyzing free-text clinical notes in the electronic medical record, while maintaining the temporal visit sequence. In a single framework, we integrated semantic data mapping and neural embedding technique to produce a text processing method that extracts relevant information from heterogeneous types of clinical notes in an unsupervised manner, and we designed a recurrent neural network to model the te"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.03058","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":""},"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":"2026-05-18T00:10:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LJYiTcRaDsqhpLxxqE8NF188Am8kJ04SO5XFgYPpIkjyWGfpxIIVvicW+ho3GZmcyifx76pyPpSiExEqvzOABw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T01:17:08.752600Z"},"content_sha256":"6b305c7bc19a8afc38a398fea6761476d0fc1bcf91e654b9ee3669bc672ed098","schema_version":"1.0","event_id":"sha256:6b305c7bc19a8afc38a398fea6761476d0fc1bcf91e654b9ee3669bc672ed098"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/THVJNQHRVIG7UN4S3DWWP5NBO7/bundle.json","state_url":"https://pith.science/pith/THVJNQHRVIG7UN4S3DWWP5NBO7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/THVJNQHRVIG7UN4S3DWWP5NBO7/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":"2026-06-08T01:17:08Z","links":{"resolver":"https://pith.science/pith/THVJNQHRVIG7UN4S3DWWP5NBO7","bundle":"https://pith.science/pith/THVJNQHRVIG7UN4S3DWWP5NBO7/bundle.json","state":"https://pith.science/pith/THVJNQHRVIG7UN4S3DWWP5NBO7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/THVJNQHRVIG7UN4S3DWWP5NBO7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:THVJNQHRVIG7UN4S3DWWP5NBO7","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":"ac34dfc3e6cea98b8194025a8433e011c651196d8c90df30a7b18a738090a7c3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-01-09T17:51:12Z","title_canon_sha256":"c8e8fa4987af8f5d1329c73f7b89acd159de61b3a366ecb0db42e1a222911ddb"},"schema_version":"1.0","source":{"id":"1801.03058","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.03058","created_at":"2026-05-18T00:10:46Z"},{"alias_kind":"arxiv_version","alias_value":"1801.03058v2","created_at":"2026-05-18T00:10:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.03058","created_at":"2026-05-18T00:10:46Z"},{"alias_kind":"pith_short_12","alias_value":"THVJNQHRVIG7","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"THVJNQHRVIG7UN4S","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"THVJNQHR","created_at":"2026-05-18T12:32:53Z"}],"graph_snapshots":[{"event_id":"sha256:6b305c7bc19a8afc38a398fea6761476d0fc1bcf91e654b9ee3669bc672ed098","target":"graph","created_at":"2026-05-18T00:10:46Z","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":"We propose a deep learning model - Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) for estimating short-term life expectancy (3 months) of the patients by analyzing free-text clinical notes in the electronic medical record, while maintaining the temporal visit sequence. In a single framework, we integrated semantic data mapping and neural embedding technique to produce a text processing method that extracts relevant information from heterogeneous types of clinical notes in an unsupervised manner, and we designed a recurrent neural network to model the te","authors_text":"Daniel Chang, Daniel L. Rubin, Douglas J. Wood, Imon Banerjee, Michael Francis Gensheimer, Solomon Henry","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-01-09T17:51:12Z","title":"Abstract: Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.03058","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:b866a83b78d3b94abfbb3ba991e25b51681b2d42da02105b957f78edff5109d2","target":"record","created_at":"2026-05-18T00:10:46Z","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":"ac34dfc3e6cea98b8194025a8433e011c651196d8c90df30a7b18a738090a7c3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-01-09T17:51:12Z","title_canon_sha256":"c8e8fa4987af8f5d1329c73f7b89acd159de61b3a366ecb0db42e1a222911ddb"},"schema_version":"1.0","source":{"id":"1801.03058","kind":"arxiv","version":2}},"canonical_sha256":"99ea96c0f1aa0dfa3792d8ed67f5a177ef8f30d07d56b3b9e95d2a938d630f71","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"99ea96c0f1aa0dfa3792d8ed67f5a177ef8f30d07d56b3b9e95d2a938d630f71","first_computed_at":"2026-05-18T00:10:46.961732Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:10:46.961732Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VMBG4tzlEoPGHIOjEaqIsCNHGj84aQU0BqCX0USbizxKSiK20/4wWQ3FIOt5Mqi/Ki+l+idBL3dXP+kPSspYBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:10:46.962552Z","signed_message":"canonical_sha256_bytes"},"source_id":"1801.03058","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b866a83b78d3b94abfbb3ba991e25b51681b2d42da02105b957f78edff5109d2","sha256:6b305c7bc19a8afc38a398fea6761476d0fc1bcf91e654b9ee3669bc672ed098"],"state_sha256":"d9910676e8771cb55bc5ba4ce6b0cf28daf8c75121b38b52ecacef7954989f21"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6jmYAADxkHUmkbkgZlIR6LF7RZCQIE4A7T3CEgXU30eryxlyZX0LVGhcs8GK5i6aYFTSKUoBDoRrx2q0/iijBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T01:17:08.754728Z","bundle_sha256":"b0808bd5eb75589a9558029fe3315b623d3c2e221300b2107de72916c1a64745"}}