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Paper Citation Record · LEDGER

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways

As of 7 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2508.07308.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.07308 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:15:09.898848Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T16:14:18.164403Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T01:57:32.123183Z

Reference resolution

52 of 52 outbound references displayed

  • verified exact2
  • verified fuzzy18
  • unresolved31
  • parse uncertain1
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 52a55cba-67d0-4366-8538-594f783b9ac9 · outbound

This paper cites GPT-4 Technical Report.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways GPT-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-05T22:15:09.700858Z digest=sha256:de4344f04c20991018042f8e68db177c404005d0301b78c8e86297ebcc5037d3

Observation b0f28552-57db-4a2b-89f6-e612755ef227 · outbound

This paper cites A Comprehensive Overview of Large Language Models.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways A Comprehensive Overview of Large Language Models

Reference 2

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no resolver link, observed 2026-08-05T22:15:09.705004Z

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source=pdf_text observed=2026-08-05T22:15:09.705004Z digest=sha256:fe535c69d721af26f94165a06745e4201f3c59c7f6aedc0da93f5e9cd2050ef6

Observation 48cf0928-8943-4f45-9767-37cb06d4547e · outbound

This paper cites Unifying Large Language Models and Knowledge Graphs: A Roadmap.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Unifying Large Language Models and Knowledge Graphs: A Roadmap

Reference 3

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source=pdf_text observed=2026-08-05T22:15:09.709334Z digest=sha256:24a5d1543bf0ee03af41138b7a1f3062cb6841818397950815bfcc522eb4aef2

Observation 5f902965-1f77-467a-b735-b40b793ebd0c · outbound

This paper cites Role of chat gpt in public health.Annals of biomedical engineering, 51(5):868–869, 2023.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Role of chat gpt in public health.Annals of biomedical engineering, 51(5):868–869, 2023

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.447020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.713285Z digest=sha256:bdfe50c58c8994b2034a6467f82a3a4c7c48f06ed18acb4736152b5ff1f556f9

Observation e3f87fdd-46fc-48a0-98fb-6c75b068c491 · outbound

This paper cites Benchmarking Retrieval-Augmented Generation for Medicine.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Benchmarking Retrieval-Augmented Generation for Medicine

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.717218Z digest=sha256:f7159f1d3a8c935eb9fd4ae08b75639ef88ce326515e6126d3d191576984b016

Observation 35cde59d-842f-4914-aa34-6d39486c5bec · outbound

This paper cites A survey on rag with llms.Procedia Computer Science, 246:3781–3790, 2024.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways A survey on rag with llms.Procedia Computer Science, 246:3781–3790, 2024

Reference 6

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raw_fallback, observed 2026-08-05T22:15:10.435730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.721402Z digest=sha256:798d96cd4c616323cd35dc89cfb7832f1e8451f907f4f92af03a9c4cf7a6fa1c

Observation 7c3333ae-4a14-43b7-808e-7ee5e2c5baec · outbound

This paper cites Medical Dialogue: A Survey of Categories, Methods, Evaluation and Challenges.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Medical Dialogue: A Survey of Categories, Methods, Evaluation and Challenges

Reference 7

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verified exact
local_arxiv, observed 2026-08-05T22:15:10.155055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.725532Z digest=sha256:771c7c0111eb66cef28598429b5712981037d26aa0571c9c648cab14854c5b32

Observation a05bf3a0-e8ab-4031-941b-f2b70c36ffd3 · outbound

This paper cites Extract- ing training data from large language models.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Extract- ing training data from large language models

Reference 8

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raw_fallback, observed 2026-08-05T22:15:10.424558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.730009Z digest=sha256:b35fbe98a0c9c41f952983d698230f4c29aa5d8740b38d66b4855ab2f2b74631

Observation 4b548cd2-bf4e-4cf5-8a8f-09030a3e1df1 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Direct preference optimization: Your language model is secretly a reward model

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.733993Z digest=sha256:6972248176e178dd554d80dc5d7b6cc922291f0a9646257806bcb587d9fa1748

Observation f1ce7d53-94de-4f0c-8599-07a826ef19b2 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in Neural Information Processing Systems, 33:9459–9474, 2020.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in Neural Information Processing Systems, 33:9459–9474, 2020

Reference 10

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source=pdf_text observed=2026-08-05T22:15:09.737403Z digest=sha256:6eafd3b09bc32f54327fc7f218f4faae6a69a4529a460fc5f06750b79614ff32

Observation c6b1946a-d7de-4bf5-a86b-0d3813b4426a · outbound

This paper cites Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing.ACM Computing Surveys, 55(9):1–35, 2023.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing.ACM Computing Surveys, 55(9):1–35, 2023

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.400111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.740686Z digest=sha256:97d0eb38e87559571a57769b9dba269c0ae1bb44c870e41e03c4639444a2026d

Observation e8c253ae-a0f4-4172-803a-0ed99140fe1c · outbound

This paper cites Retrieval augmented language model pre-training.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Retrieval augmented language model pre-training

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.744215Z digest=sha256:6cf7091d3cac58d94193d01cf52748c5b34bef15a9ee8f6e58e021e940348740

Observation f58a69a5-2c1f-48bd-9514-d45d7168163e · outbound

This paper cites Atlas: Few-shot learning with retrieval augmented language models.Journal of Machine Learning Research, 24(251):1–43, 2023.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Atlas: Few-shot learning with retrieval augmented language models.Journal of Machine Learning Research, 24(251):1–43, 2023

Reference 13

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raw_fallback, observed 2026-08-05T22:15:10.382576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.748222Z digest=sha256:463b870d2a317904e1e1b1ce33b0f44df8e2e63345cbd37de555573982c90013

Observation 5ed4a2df-d488-45b0-8f3f-edd0337cce11 · outbound

This paper cites Retrieving Supporting Evidence for LLMs Generated Answers.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Retrieving Supporting Evidence for LLMs Generated Answers

Reference 14

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T22:15:09.752027Z digest=sha256:daa110153b472c1e3de319765c9380d172776e63976f5d016149b1fda6ac71dd

Observation 3bef35ef-1e42-4b3a-be61-830d1c9dfb68 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 15

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source=pdf_text observed=2026-08-05T22:15:09.755768Z digest=sha256:0a846f54dca94e4da4c8a287160dd9b838efd5c70e959a2f5a18f4d373263072

Observation a61af990-ee50-4efc-a8dc-3021f7dbfcd3 · outbound

This paper cites Health-LLM: Personalized Retrieval-Augmented Disease Prediction System.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Health-LLM: Personalized Retrieval-Augmented Disease Prediction System

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.760293Z digest=sha256:5a037e3e49acd5af129da2b46f323c556b25b4a0ad76baeb10d9123b5e3cebb0

Observation f4fa7d9d-b205-444e-b6e1-ec2955b01414 · outbound

This paper cites HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations

Reference 17

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source=pdf_text observed=2026-08-05T22:15:09.763907Z digest=sha256:c8e920fbf4e9ea3d461b0e75ec7445e8ccf9a758e3664f94da7d03024155b6aa

Observation 46cdd1c6-3098-4c1c-94a3-8237d206aa50 · outbound

This paper cites Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology

Reference 18

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local_arxiv, observed 2026-08-05T22:15:10.100836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.767547Z digest=sha256:ab981dd84f95300d3a02acbc3499cf6703c9efa5566afdbb3a6481f6b8d6409c

Observation d336674c-dcd5-4b24-a79b-e28b9cbd8923 · outbound

This paper cites Graph retrieval-augmented generation for large language models: A survey.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Graph retrieval-augmented generation for large language models: A survey

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.371409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.771480Z digest=sha256:bc127234553b67e45dbbfd52fe2e3d980288e995b22b5fa284ec538f089ebf79

Observation 000a6337-85ba-4db3-915c-847e61b3448a · outbound

This paper cites medIKAL: Integrating Knowledge Graphs as Assistants of LLMs for Enhanced Clinical Diagnosis on EMRs.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways medIKAL: Integrating Knowledge Graphs as Assistants of LLMs for Enhanced Clinical Diagnosis on EMRs

Reference 20

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source=pdf_text observed=2026-08-05T22:15:09.774911Z digest=sha256:598a46cf11bc4182da2b1f4bedb8b856e128268ab0d02d534ccd24dc9c7b7cb4

Observation ed7fe314-f1d8-4bd1-8b81-f54a1a5136c0 · outbound

This paper cites Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation

Reference 21

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source=pdf_text observed=2026-08-05T22:15:09.778474Z digest=sha256:57b3b21f9521837f3565a220b0233ba572621b769848abef6f0be7705952e9a4

Observation f93b319c-adbe-439a-bbad-8eb8a1602f6f · outbound

This paper cites Leveraging retrieval-augmented generation for reliable medical question answering using large language models.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Leveraging retrieval-augmented generation for reliable medical question answering using large language models

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.359574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.782088Z digest=sha256:87dc78de27e3c43ed325b4d110ef6ecde9a3861b776c6175c47d2ddb0c6ce564

Observation 3a3d6e19-488a-40f7-b754-b4d05b56428a · outbound

This paper cites HEAD-QA: A Healthcare Dataset for Complex Reasoning.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways HEAD-QA: A Healthcare Dataset for Complex Reasoning

Reference 23

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T22:15:09.785590Z digest=sha256:c4652b6e50703a0c62e32bdca42487c083be5f5151c777c44d842fab60fe5abc

Observation e8dd7352-0cf5-4239-8fff-d5ad575f5307 · outbound

This paper cites MeDiaQA: A Question Answering Dataset on Medical Dialogues.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways MeDiaQA: A Question Answering Dataset on Medical Dialogues

Reference 24

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source=pdf_text observed=2026-08-05T22:15:09.789267Z digest=sha256:149d4df8da5593a95e78deb0a0a39c9dc0f7a35d899ce02c55f9dd096c546b43

Observation ab22f3d4-f4a1-41af-bf3b-9a6fa15e8065 · outbound

This paper cites What disease does this patient have? a large-scale open domain question answering dataset from medical exams.Applied Sciences, 11(14):6421, 2021.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways What disease does this patient have? a large-scale open domain question answering dataset from medical exams.Applied Sciences, 11(14):6421, 2021

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.793387Z digest=sha256:c89f183f21f612d4de872611a1abb6b74975e26e6a3f21ce276798ff7cb36f84

Observation ff1ed2d5-8daa-4bb9-a8fc-81dbf35ed8bd · outbound

This paper cites Pub- medqa: A dataset for biomedical research question answering.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Pub- medqa: A dataset for biomedical research question answering

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.341584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.796669Z digest=sha256:460df681d039a794656c9924a78bbd2836be6e1a11d1cbc79acde70f337ed095

Observation 59b8af93-c29a-488b-8b3d-56849203a6b8 · outbound

This paper cites Medcalc-bench: Evaluating large language models for medical calculations.Advances in Neural Information Processing Systems, 37:84730–84745, 2024.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Medcalc-bench: Evaluating large language models for medical calculations.Advances in Neural Information Processing Systems, 37:84730–84745, 2024

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.330807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.800015Z digest=sha256:5720107ec3a9d49b5c57b52d773c655a0a5b727dfd8654abf8ac770e67135aaf

Observation dd5a822a-8d12-47b1-91a2-6922c53db6fa · outbound

This paper cites PathVQA: 30000+ Questions for Medical Visual Question Answering.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways PathVQA: 30000+ Questions for Medical Visual Question Answering

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.804058Z digest=sha256:46b551a158d237c92a3b1dae6eeade1273b15784cf1301e5deea0c91caffc55b

Observation 79c74b63-3575-4107-a71c-1c6a7baa8a60 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Measuring Massive Multitask Language Understanding

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.808044Z digest=sha256:0f8191910014fb05f7dc8fe2bb979fa9e351ed5cf6f3f774bb58b602f2402c5f

Observation 095c61c5-541d-402c-bfe5-81fd8a7f004f · outbound

This paper cites MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding

Reference 30

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no resolver link, observed 2026-08-05T22:15:09.811969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.811969Z digest=sha256:35997dccbba34c9548abb1e4dbb5c2a36fa0a7ac95ed97eb31c01c6fadc03b38

Observation 7866e88d-2c80-478e-bfd1-6336e1c3debe · outbound

This paper cites Knowledge graph-based question answering with electronic health records.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Knowledge graph-based question answering with electronic health records

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.318056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.815778Z digest=sha256:560d169b9abac6e84bdba1be25179f64a69bda5b2f963d87a9f4a9030d3a9b03

Observation 503e2e58-3d08-4498-b4e2-90ffb1302189 · outbound

This paper cites Ultramedical: Building specialized generalistsinbiomedicine.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Ultramedical: Building specialized generalistsinbiomedicine

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.306110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.820612Z digest=sha256:52d0fb1623e052aebbc0256ba7389e2f3d09e9db34cd49a57527ae9a6f260a0f

Observation 25f7555e-1606-48bb-bd07-5e3106850c4d · outbound

This paper cites Sm3-text-to-query: Synthetic multi-model medical text-to-query benchmark.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Sm3-text-to-query: Synthetic multi-model medical text-to-query benchmark

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.295299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.824835Z digest=sha256:2f3eeb009c0debb17e09cf7eebd66319c40ca2e058a12205385172083a862e7c

Observation 77d03735-fb39-4154-9b88-12af56d59b4e · outbound

This paper cites Elsevier Health Sciences, 2009.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Elsevier Health Sciences, 2009

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.284644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.828137Z digest=sha256:c15c57c2c46875217503edf93ea03fee51bc2bc65437d68c37e33d7365db616e

Observation 004d8eb8-31dc-4980-80f7-586b6d45b9f7 · outbound

This paper cites Algorithms for emergency medicine.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Algorithms for emergency medicine

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.273749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.831531Z digest=sha256:4196e8b680bd5b12c39f8dfed2a9412d483c83f18e153bf6fb113badaa6c711c

Observation a19e8a24-b35f-4890-9a0d-2676fb522f6a · outbound

This paper cites Elsevier Health Sciences, 2021.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Elsevier Health Sciences, 2021

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.263117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.835133Z digest=sha256:3910a9852d41cb51b069707d046bc26327fd3383fb3ddaa374079c907e0bc69a

Observation be648ffa-66e1-4d6c-a16a-141a8c6a0ab6 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Gemini: A Family of Highly Capable Multimodal Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.838549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.838549Z digest=sha256:c3080fb90dc2080989c9117b0e302a9a20e4460d48508e4f9f8d6cd5bc5efddf

Observation a3b03bf9-d650-4901-8ba4-57d03487093d · outbound

This paper cites Identifying and mitigating vulnerabilities in llm-integrated applications.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Identifying and mitigating vulnerabilities in llm-integrated applications

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.846820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.846820Z digest=sha256:9de1002ab9c4bc1f931a00d4c028124b654684c56f7385f906014062f2bfc5e1

Observation a65f439e-3560-4b63-b5c8-d6969a811296 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.850141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.850141Z digest=sha256:28c66c0713b8534e16a758afff462eca52b17b76cd2442a8a5cbac8bc9f6a4d3

Observation 64196f21-aa6a-4a2e-a73c-e87040672d17 · outbound

This paper cites The Llama 3 Herd of Models.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways The Llama 3 Herd of Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.853828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.853828Z digest=sha256:e5b83bed792c26bcec8bada8b5c179adad758262d2858ef37484c52faa8a3fbf

Observation 8be1e80f-7373-4fec-b4eb-67e49033dc46 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Gemma: Open Models Based on Gemini Research and Technology

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.858219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.858219Z digest=sha256:7f898bd98ace7b6d35e34e77df2d3f1f94b654d8c8337f3d1551c2b1210d4032

Observation 1e62783e-54b3-4bf0-b112-c0e4a6dbc514 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Gemma 2: Improving Open Language Models at a Practical Size

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.861888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.861888Z digest=sha256:9db2f49129dcdc6b665d36359c872ad7e12485b904c75c889032a01214c59ceb

Observation 6bb9ea16-76ed-40b5-a0a5-5cdd4076c964 · outbound

This paper cites Gemma 3 Technical Report.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Gemma 3 Technical Report

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.865915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.865915Z digest=sha256:f4e41a515bc72ce605f65e1f12fd78c7cbaf33dd7fa51f9160234fa039938415

Observation 81fe91f4-02b5-4213-949a-93b3d895775d · outbound

This paper cites Qwen2.5 Technical Report.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Qwen2.5 Technical Report

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.869604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.869604Z digest=sha256:317856e62bcdd63654b91c96a1bb594c93ae5c06f8ba4d8f5f4ae34946ea1762

Observation 8e8e6163-725e-4b11-93f5-c7f8bc6eb09d · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.873050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.873050Z digest=sha256:bd8b09cc4bc24ba65003753bf0dd681bb900eb1765d7a8dfda37f41b360772c4

Observation 8f30269d-5663-4552-88c0-8bf442d3f33c · outbound

This paper cites Phi-4 Technical Report.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Phi-4 Technical Report

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.876647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.876647Z digest=sha256:728134a8324e74d2b54259be389c95ab178c39cf3be3c9d7acf98e56fd93c17c

Observation f597ec7f-287d-422d-b6b2-391fadb5b925 · outbound

This paper cites an unresolved cited work.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Unresolved cited work

Reference 49

Resolution
parse uncertain
raw_fallback, observed 2026-08-05T22:15:10.245758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.881078Z digest=sha256:f38e176e018ec493b1b1e6f9744a268b766c10714bcd9eae74c02af9824e118f

Observation caa57769-604f-4579-99b7-3d7793733887 · outbound

This paper cites G-eval: NLG evaluation using gpt-4 with better human alignment.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways G-eval: NLG evaluation using gpt-4 with better human alignment

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.884534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.884534Z digest=sha256:aaa3a4dea80a32cb34e7011a7a13951eab47da1b98b77c89d1b4bc9d32b9d065

Observation 2db0d703-8dc4-4b5f-abbb-92ba651707cc · outbound

This paper cites M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-05T22:15:09.888039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:15:09.888039Z digest=sha256:e64360aa4bee7c36930ef70bc4e651661633f28e85ec3196e5c09fb5a0fc33cd

Observation acd0bdbd-b715-4d50-8e51-512b92c7e85a · outbound

This paper cites Lessons learned from the chameleon testbed.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Lessons learned from the chameleon testbed

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.226504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.891666Z digest=sha256:540440ec6b1e33cf681d210b32a953116f5c591deec61d2fc2c58bbfb44b7dba

Observation 1201b530-d759-4a5f-b012-dade49b5e464 · outbound

This paper cites It has to be structured as a decision tree.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways It has to be structured as a decision tree

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.214740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.895173Z digest=sha256:ddc0ef9d17822fcf39a34ecc7f04025ebbb73507bd9729d134fe430fb3722236

Observation 82fff41f-ad02-40b5-bb54-4ed8ee4a4fc6 · outbound

This paper cites Make sure that you don’t get ’Invalid control character at line’ errors.

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways Make sure that you don’t get ’Invalid control character at line’ errors

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T22:15:10.204175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-08-05T22:15:09.898848Z digest=sha256:2900142adef8fee00c0c65640622e601a5be23a54726707216ea8de08e97ad5a

Pith citing papers

Observation d22fee2d-262a-4138-a9fb-54042ea76fdf · inbound

LLM-Orchestrated Conformance Checking in Stroke Care Without Computer-Interpretable Guidelines cites this paper.

LLM-Orchestrated Conformance Checking in Stroke Care Without Computer-Interpretable Guidelines HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-03T01:57:32.124810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-27T16:14:18.164403Z digest=sha256:beeea59c4d7393d64c83640e928b0a8260fa1400fff0de222449a83795ff9fed