{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:C2QG3UTXIXWFR52GB7WF6HLVQI","short_pith_number":"pith:C2QG3UTX","canonical_record":{"source":{"id":"1712.00654","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T18:39:12Z","cross_cats_sorted":[],"title_canon_sha256":"a2357aa18145876042ce4855d23051204e4b90dc9e291de8a402f99acd493045","abstract_canon_sha256":"67d8e823d6b0c21bf01b68f036299ff9eb6fa36a1459f782dff287b759e85c48"},"schema_version":"1.0"},"canonical_sha256":"16a06dd27745ec58f7460fec5f1d758221921194dc25e324779e48378fc285c5","source":{"kind":"arxiv","id":"1712.00654","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.00654","created_at":"2026-05-18T00:29:02Z"},{"alias_kind":"arxiv_version","alias_value":"1712.00654v1","created_at":"2026-05-18T00:29:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.00654","created_at":"2026-05-18T00:29:02Z"},{"alias_kind":"pith_short_12","alias_value":"C2QG3UTXIXWF","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"C2QG3UTXIXWFR52G","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"C2QG3UTX","created_at":"2026-05-18T12:31:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:C2QG3UTXIXWFR52GB7WF6HLVQI","target":"record","payload":{"canonical_record":{"source":{"id":"1712.00654","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T18:39:12Z","cross_cats_sorted":[],"title_canon_sha256":"a2357aa18145876042ce4855d23051204e4b90dc9e291de8a402f99acd493045","abstract_canon_sha256":"67d8e823d6b0c21bf01b68f036299ff9eb6fa36a1459f782dff287b759e85c48"},"schema_version":"1.0"},"canonical_sha256":"16a06dd27745ec58f7460fec5f1d758221921194dc25e324779e48378fc285c5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:02.288725Z","signature_b64":"Mcx2JON268VovjsRECW9ITmXclTRM1XEgR9WGNEuTZKM8IrceNq4jp8qB2RKO4wq16uwEbKyiK46hItKZZ2/CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"16a06dd27745ec58f7460fec5f1d758221921194dc25e324779e48378fc285c5","last_reissued_at":"2026-05-18T00:29:02.288295Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:02.288295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.00654","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":"2026-05-18T00:29:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2FFJcsRYZhXRxa77YaYJnSnwxJ2Yesu8H0C6Byg5y0WteB58B7ZbXMGC98YQoy7TwkF0CxF6rj6CM1UhDJjkCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T23:22:36.606310Z"},"content_sha256":"3f1a752299542d7702a07bc4386444b0e2d1b923bf4f6ee966843f73a94116a6","schema_version":"1.0","event_id":"sha256:3f1a752299542d7702a07bc4386444b0e2d1b923bf4f6ee966843f73a94116a6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:C2QG3UTXIXWFR52GB7WF6HLVQI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Representation and Reinforcement Learning for Personalized Glycemic Control in Septic Patients","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Mingwu Gao, Peter Szolovits, Susu Yan, Wei-Hung Weng, Ze He","submitted_at":"2017-12-02T18:39:12Z","abstract_excerpt":"Glycemic control is essential for critical care. However, it is a challenging task because there has been no study on personalized optimal strategies for glycemic control. This work aims to learn personalized optimal glycemic trajectories for severely ill septic patients by learning data-driven policies to identify optimal targeted blood glucose levels as a reference for clinicians. We encoded patient states using a sparse autoencoder and adopted a reinforcement learning paradigm using policy iteration to learn the optimal policy from data. We also estimated the expected return following the p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.00654","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":"2026-05-18T00:29:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qhuI54sFpFTtnkylMbjIkk6Itw5E5+IRS/1fgY6sXsNDZMUn4NL0NEax862+RF530lp6D3o9DVtMujTFtGsmAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T23:22:36.607025Z"},"content_sha256":"b56f168310c7c26a7db79f691e42ed6a5a05abc0aef637801073323fae04f761","schema_version":"1.0","event_id":"sha256:b56f168310c7c26a7db79f691e42ed6a5a05abc0aef637801073323fae04f761"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C2QG3UTXIXWFR52GB7WF6HLVQI/bundle.json","state_url":"https://pith.science/pith/C2QG3UTXIXWFR52GB7WF6HLVQI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C2QG3UTXIXWFR52GB7WF6HLVQI/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":"2026-05-25T23:22:36Z","links":{"resolver":"https://pith.science/pith/C2QG3UTXIXWFR52GB7WF6HLVQI","bundle":"https://pith.science/pith/C2QG3UTXIXWFR52GB7WF6HLVQI/bundle.json","state":"https://pith.science/pith/C2QG3UTXIXWFR52GB7WF6HLVQI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C2QG3UTXIXWFR52GB7WF6HLVQI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:C2QG3UTXIXWFR52GB7WF6HLVQI","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":"67d8e823d6b0c21bf01b68f036299ff9eb6fa36a1459f782dff287b759e85c48","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T18:39:12Z","title_canon_sha256":"a2357aa18145876042ce4855d23051204e4b90dc9e291de8a402f99acd493045"},"schema_version":"1.0","source":{"id":"1712.00654","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.00654","created_at":"2026-05-18T00:29:02Z"},{"alias_kind":"arxiv_version","alias_value":"1712.00654v1","created_at":"2026-05-18T00:29:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.00654","created_at":"2026-05-18T00:29:02Z"},{"alias_kind":"pith_short_12","alias_value":"C2QG3UTXIXWF","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"C2QG3UTXIXWFR52G","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"C2QG3UTX","created_at":"2026-05-18T12:31:08Z"}],"graph_snapshots":[{"event_id":"sha256:b56f168310c7c26a7db79f691e42ed6a5a05abc0aef637801073323fae04f761","target":"graph","created_at":"2026-05-18T00:29:02Z","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":"Glycemic control is essential for critical care. However, it is a challenging task because there has been no study on personalized optimal strategies for glycemic control. This work aims to learn personalized optimal glycemic trajectories for severely ill septic patients by learning data-driven policies to identify optimal targeted blood glucose levels as a reference for clinicians. We encoded patient states using a sparse autoencoder and adopted a reinforcement learning paradigm using policy iteration to learn the optimal policy from data. We also estimated the expected return following the p","authors_text":"Mingwu Gao, Peter Szolovits, Susu Yan, Wei-Hung Weng, Ze He","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T18:39:12Z","title":"Representation and Reinforcement Learning for Personalized Glycemic Control in Septic Patients"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.00654","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":"sha256:3f1a752299542d7702a07bc4386444b0e2d1b923bf4f6ee966843f73a94116a6","target":"record","created_at":"2026-05-18T00:29:02Z","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":"67d8e823d6b0c21bf01b68f036299ff9eb6fa36a1459f782dff287b759e85c48","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-02T18:39:12Z","title_canon_sha256":"a2357aa18145876042ce4855d23051204e4b90dc9e291de8a402f99acd493045"},"schema_version":"1.0","source":{"id":"1712.00654","kind":"arxiv","version":1}},"canonical_sha256":"16a06dd27745ec58f7460fec5f1d758221921194dc25e324779e48378fc285c5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"16a06dd27745ec58f7460fec5f1d758221921194dc25e324779e48378fc285c5","first_computed_at":"2026-05-18T00:29:02.288295Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:29:02.288295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Mcx2JON268VovjsRECW9ITmXclTRM1XEgR9WGNEuTZKM8IrceNq4jp8qB2RKO4wq16uwEbKyiK46hItKZZ2/CA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:29:02.288725Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.00654","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3f1a752299542d7702a07bc4386444b0e2d1b923bf4f6ee966843f73a94116a6","sha256:b56f168310c7c26a7db79f691e42ed6a5a05abc0aef637801073323fae04f761"],"state_sha256":"f8f73da897bb2879e2343b77c33940d39ecb15d8f92881ba075c47169ba9e73b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Hl7OaluCVKLMuG8+GbB2tp4LMgORoZtPa//Y2a6vrFEVpRBQDOFlJJWFjDHWHUo+xrVXXgrVQ0VFDP0b58UcBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T23:22:36.610753Z","bundle_sha256":"5afc1b549a6bca6cbc4ef623f8893ca7f4755ae14b2b85ae3e8ea43acd899123"}}