Pith Number

pith:YLCNGINI

pith:2026:YLCNGINIAXAOKFCDVSOMDF3LB6

not attested not anchored not stored refs pending

Learning Preference-Based Objectives from Clinical Narratives for Dynamic Sepsis Treatment

Arturo Yong Yao Neo, Daniel J. Tan, Jayne Hui Zhen Chan, Kai Wen Hwang, Kay Choong See, Mengling Feng

Clinical narratives supply preference signals that train rewards yielding better recovery in sequential treatment policies.

arxiv:2604.10783 v2 · 2026-04-12 · cs.AI · cs.LG

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\usepackage{pith}
\pithnumber{YLCNGINIAXAOKFCDVSOMDF3LB6}

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Record completeness

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

The learned reward aligns strongly with trajectory quality (Spearman rho = 0.63) and enables policies that are consistently associated with improved recovery-related outcomes, including increased organ support-free days and faster shock resolution, while maintaining comparable performance on mortality. These effects persist under external validation.

C2weakest assumption

That LLM-derived trajectory quality scores and pairwise preferences from discharge summaries accurately and unbiasedly reflect true clinical trajectory quality, patient preferences, and treatment effectiveness without significant influence from narrative variability, LLM biases, or selection effects in the data.

C3one line summary

CN-PR learns reward functions from LLM-derived preferences over clinical trajectories to improve RL policies for sequential treatment decisions, showing correlation with quality scores and better recovery outcomes.

Receipt and verification

First computed	2026-05-26T02:05:09.220173Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

c2c4d321a805c0e51443ac9cc1976b0fa1ef2c09358c360a5099042273c755f3

Aliases

arxiv: 2604.10783 · arxiv_version: 2604.10783v2 · doi: 10.48550/arxiv.2604.10783 · pith_short_12: YLCNGINIAXAO · pith_short_16: YLCNGINIAXAOKFCD · pith_short_8: YLCNGINI

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/YLCNGINIAXAOKFCDVSOMDF3LB6 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: c2c4d321a805c0e51443ac9cc1976b0fa1ef2c09358c360a5099042273c755f3

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "000828a8122a2c5b0e0f458508872216a5f59f3907c99e9daa8457c173ecbd7b",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-04-12T19:18:02Z",
    "title_canon_sha256": "9783c1112bd70d73fbe1e612a52a75ce9b5e47e274b99ecd93bc73b9581ce887"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.10783",
    "kind": "arxiv",
    "version": 2
  }
}