{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:I323CTXZYUMJLQ635PN7WUXX64","short_pith_number":"pith:I323CTXZ","canonical_record":{"source":{"id":"1905.10705","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-05-26T01:16:36Z","cross_cats_sorted":["cs.LG","q-bio.QM","stat.ME"],"title_canon_sha256":"1ded062434809812079aabf8d973e79cd53286a2d3816e17bb3a3542d9137ca2","abstract_canon_sha256":"cc4f8fc24112e7d1756729f4fa23a260939d7ce27cee4fdb6e4905af05ccaa05"},"schema_version":"1.0"},"canonical_sha256":"46f5b14ef9c51895c3dbebdbfb52f7f73eac4797f452cae2f6e7035badb7db77","source":{"kind":"arxiv","id":"1905.10705","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.10705","created_at":"2026-05-17T23:45:05Z"},{"alias_kind":"arxiv_version","alias_value":"1905.10705v1","created_at":"2026-05-17T23:45:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.10705","created_at":"2026-05-17T23:45:05Z"},{"alias_kind":"pith_short_12","alias_value":"I323CTXZYUMJ","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"I323CTXZYUMJLQ63","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"I323CTXZ","created_at":"2026-05-18T12:33:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:I323CTXZYUMJLQ635PN7WUXX64","target":"record","payload":{"canonical_record":{"source":{"id":"1905.10705","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-05-26T01:16:36Z","cross_cats_sorted":["cs.LG","q-bio.QM","stat.ME"],"title_canon_sha256":"1ded062434809812079aabf8d973e79cd53286a2d3816e17bb3a3542d9137ca2","abstract_canon_sha256":"cc4f8fc24112e7d1756729f4fa23a260939d7ce27cee4fdb6e4905af05ccaa05"},"schema_version":"1.0"},"canonical_sha256":"46f5b14ef9c51895c3dbebdbfb52f7f73eac4797f452cae2f6e7035badb7db77","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:45:05.525278Z","signature_b64":"JBnCbmB70uBGAHWJ4q6fI9eQDvbfJ0DiWCoKrSOR42SJ3BEso0X1vcMI0fwpIzj1S5KP2/rmknoe0pVZqk/mDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"46f5b14ef9c51895c3dbebdbfb52f7f73eac4797f452cae2f6e7035badb7db77","last_reissued_at":"2026-05-17T23:45:05.524743Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:45:05.524743Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.10705","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:45:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TeUjqjqS1Q6Sy+CKa913A0vG43yi4oopUazlb9ZqJADB07nwEtbk57191yX01EcAsTRiMD3PwkrGvxgeOmXzBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T23:37:39.062652Z"},"content_sha256":"9a7246c0343a31d75f46f7845846f03a4d625d028cd844e86f64d0649f87a0ba","schema_version":"1.0","event_id":"sha256:9a7246c0343a31d75f46f7845846f03a4d625d028cd844e86f64d0649f87a0ba"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:I323CTXZYUMJLQ635PN7WUXX64","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Modeling treatment events in disease progression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","q-bio.QM","stat.ME"],"primary_cat":"stat.ML","authors_text":"Guanyang Wang, {\\L}ukasz Kidzi\\'nski, Xuxin Huang, Yong Deng, Yumeng Zhang","submitted_at":"2019-05-26T01:16:36Z","abstract_excerpt":"Ability to quantify and predict progression of a disease is fundamental for selecting an appropriate treatment. Many clinical metrics cannot be acquired frequently either because of their cost (e.g. MRI, gait analysis) or because they are inconvenient or harmful to a patient (e.g. biopsy, x-ray). In such scenarios, in order to estimate individual trajectories of disease progression, it is advantageous to leverage similarities between patients, i.e. the covariance of trajectories, and find a latent representation of progression. Most of existing methods for estimating trajectories do not accoun"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.10705","kind":"arxiv","version":1},"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":"2026-05-17T23:45:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sHX3hYb/ZsGYitv4PWjaCeBIFO3aXMMP1zwPKONzezvAaQ2SyeA+PBRvVMAnRZ42p/CtE6zyJNrVExwZPJCMDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T23:37:39.063294Z"},"content_sha256":"fec832209c8e71c14f82e8f51903730c558937f395a3f5b026f9ebd0d09ee999","schema_version":"1.0","event_id":"sha256:fec832209c8e71c14f82e8f51903730c558937f395a3f5b026f9ebd0d09ee999"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/I323CTXZYUMJLQ635PN7WUXX64/bundle.json","state_url":"https://pith.science/pith/I323CTXZYUMJLQ635PN7WUXX64/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/I323CTXZYUMJLQ635PN7WUXX64/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":"2026-06-07T23:37:39Z","links":{"resolver":"https://pith.science/pith/I323CTXZYUMJLQ635PN7WUXX64","bundle":"https://pith.science/pith/I323CTXZYUMJLQ635PN7WUXX64/bundle.json","state":"https://pith.science/pith/I323CTXZYUMJLQ635PN7WUXX64/state.json","well_known_bundle":"https://pith.science/.well-known/pith/I323CTXZYUMJLQ635PN7WUXX64/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:I323CTXZYUMJLQ635PN7WUXX64","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":"cc4f8fc24112e7d1756729f4fa23a260939d7ce27cee4fdb6e4905af05ccaa05","cross_cats_sorted":["cs.LG","q-bio.QM","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-05-26T01:16:36Z","title_canon_sha256":"1ded062434809812079aabf8d973e79cd53286a2d3816e17bb3a3542d9137ca2"},"schema_version":"1.0","source":{"id":"1905.10705","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.10705","created_at":"2026-05-17T23:45:05Z"},{"alias_kind":"arxiv_version","alias_value":"1905.10705v1","created_at":"2026-05-17T23:45:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.10705","created_at":"2026-05-17T23:45:05Z"},{"alias_kind":"pith_short_12","alias_value":"I323CTXZYUMJ","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"I323CTXZYUMJLQ63","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"I323CTXZ","created_at":"2026-05-18T12:33:18Z"}],"graph_snapshots":[{"event_id":"sha256:fec832209c8e71c14f82e8f51903730c558937f395a3f5b026f9ebd0d09ee999","target":"graph","created_at":"2026-05-17T23:45:05Z","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":"Ability to quantify and predict progression of a disease is fundamental for selecting an appropriate treatment. Many clinical metrics cannot be acquired frequently either because of their cost (e.g. MRI, gait analysis) or because they are inconvenient or harmful to a patient (e.g. biopsy, x-ray). In such scenarios, in order to estimate individual trajectories of disease progression, it is advantageous to leverage similarities between patients, i.e. the covariance of trajectories, and find a latent representation of progression. Most of existing methods for estimating trajectories do not accoun","authors_text":"Guanyang Wang, {\\L}ukasz Kidzi\\'nski, Xuxin Huang, Yong Deng, Yumeng Zhang","cross_cats":["cs.LG","q-bio.QM","stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-05-26T01:16:36Z","title":"Modeling treatment events in disease progression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.10705","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":"sha256:9a7246c0343a31d75f46f7845846f03a4d625d028cd844e86f64d0649f87a0ba","target":"record","created_at":"2026-05-17T23:45:05Z","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":"cc4f8fc24112e7d1756729f4fa23a260939d7ce27cee4fdb6e4905af05ccaa05","cross_cats_sorted":["cs.LG","q-bio.QM","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-05-26T01:16:36Z","title_canon_sha256":"1ded062434809812079aabf8d973e79cd53286a2d3816e17bb3a3542d9137ca2"},"schema_version":"1.0","source":{"id":"1905.10705","kind":"arxiv","version":1}},"canonical_sha256":"46f5b14ef9c51895c3dbebdbfb52f7f73eac4797f452cae2f6e7035badb7db77","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"46f5b14ef9c51895c3dbebdbfb52f7f73eac4797f452cae2f6e7035badb7db77","first_computed_at":"2026-05-17T23:45:05.524743Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:45:05.524743Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JBnCbmB70uBGAHWJ4q6fI9eQDvbfJ0DiWCoKrSOR42SJ3BEso0X1vcMI0fwpIzj1S5KP2/rmknoe0pVZqk/mDg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:45:05.525278Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.10705","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9a7246c0343a31d75f46f7845846f03a4d625d028cd844e86f64d0649f87a0ba","sha256:fec832209c8e71c14f82e8f51903730c558937f395a3f5b026f9ebd0d09ee999"],"state_sha256":"90e6665d61175f5fd9cc31e219759ee382684c484bb85d8b83d5b9ddf9da1609"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"20gYVNu+PeNtHuAAzzxjIRGWE9AdH5GCiED56fC3aD+LrLtueD3HVVkTpPQsmTotVtGznI/uLh3vGh00pDb9BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T23:37:39.066710Z","bundle_sha256":"669811f96916131f0572d8c03ded45673c2b5ffe02cffdb137a0e25f178e57f3"}}