Paper Citation Record · LEDGER

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology

As of 18 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2507.03722.

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

pith.paper-citation-record.v1
2507.03722 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:07:59.836050Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

verified exact0
verified fuzzy29
unresolved14
parse uncertain1
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 293d8b3e-6331-4f35-a5ed-a67ec7b8742d · outbound

This paper cites Nature, 2023.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Nature, 2023

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T20:07:59.689215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c150d23e-3234-4c79-8d33-8355fcc1010d · outbound

This paper cites an unresolved cited work.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:08:02.293804Z

Source-reported events for the cited work

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Observation a5c28fca-7dea-45d7-a9d0-aee2001da12f · outbound

This paper cites Language Models are Few-Shot Learners.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Language Models are Few-Shot Learners

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T20:07:59.701861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd74cce7-10d6-468d-bf08-748a4c09cfc9 · outbound

This paper cites an unresolved cited work.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:08:01.974303Z

Source-reported events for the cited work

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Observation eeecf040-217a-44b7-b8ce-156ea172f0be · outbound

This paper cites J Stomatol Oral Maxillofac Surg, 2024.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology J Stomatol Oral Maxillofac Surg, 2024

Reference 5

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Source-reported events for the cited work

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Observation 25b15701-bf8a-42f3-a170-66cc88f704f3 · outbound

This paper cites 42(4): p.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology 42(4): p

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:01.678524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 513a6f93-cd9b-4aed-ba30-edfb08d213c8 · outbound

This paper cites Digit Discov, 2023.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Digit Discov, 2023

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:01.482102Z

Source-reported events for the cited work

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Observation af68ffa0-6677-475b-9748-f11096da3602 · outbound

This paper cites an unresolved cited work.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Unresolved cited work

Reference 8

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Source-reported events for the cited work

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Observation f0c0d990-6839-47a0-9b04-b8479a460012 · outbound

This paper cites BioData Min, 2023.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology BioData Min, 2023

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:01.121991Z

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Observation 2bc0d551-1978-4177-b89e-10f18d4661bf · outbound

This paper cites Clin Transl Sci, 2025.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Clin Transl Sci, 2025

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:00.937503Z

Source-reported events for the cited work

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Observation 13f47a96-b060-458e-b94d-a61306010d09 · outbound

This paper cites LLM Agent Swarm for Hypothesis-Driven Drug Discovery.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology LLM Agent Swarm for Hypothesis-Driven Drug Discovery

Reference 11

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Source-reported events for the cited work

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Observation 71e80554-94d0-435a-bc06-0a05348a2574 · outbound

This paper cites an unresolved cited work.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Unresolved cited work

Reference 12

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Observation c022956e-fa60-4b46-92d1-feffd3a60705 · outbound

This paper cites Nature Reviews Physics, 2023.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Nature Reviews Physics, 2023

Reference 13

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Observation fcb2838b-a080-46e5-9fa3-3d3f2e595233 · outbound

This paper cites an unresolved cited work.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Unresolved cited work

Reference 14

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Source-reported events for the cited work

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Observation 74d46eb9-5515-4a99-b021-90780643102f · outbound

This paper cites an unresolved cited work.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Unresolved cited work

Reference 15

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Observation 7ece29dd-3792-4091-afb1-c8fed192ec90 · outbound

This paper cites Padmanabhan, and K.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Padmanabhan, and K

Reference 16

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Observation 6d5f8823-4da6-4b5f-8c8b-1ec0d6f5d0d5 · outbound

This paper cites Bryson, and A.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Bryson, and A

Reference 17

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Observation ace6e310-c9d6-48cf-b222-8a3715caba1a · outbound

This paper cites an unresolved cited work.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Unresolved cited work

Reference 18

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Source-reported events for the cited work

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Observation 5d6190f0-7d7a-4147-a1c3-a221069d4427 · outbound

This paper cites Res Social Adm Pharm, 2023.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Res Social Adm Pharm, 2023

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:00.221347Z

Source-reported events for the cited work

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Observation 3f678392-c53d-454b-b863-8530c0e7b3d7 · outbound

This paper cites Stephens, and F.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Stephens, and F

Reference 20

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Source-reported events for the cited work

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Observation 47951bb2-66da-4e4a-b85d-af7d0515ca2a · outbound

This paper cites PLoS Comput Biol, 2024.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology PLoS Comput Biol, 2024

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:00.185231Z

Source-reported events for the cited work

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Observation 8b43bd5a-336a-47ce-9bee-24062675b6b8 · outbound

This paper cites Am Psychol, 2018.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Am Psychol, 2018

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:00.166979Z

Source-reported events for the cited work

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Observation e59d3f78-29f0-4abd-9aeb-4945838fb9c7 · outbound

This paper cites Wang, and J.A.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Wang, and J.A

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:00.148470Z

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Observation a4a2cbe2-3200-4224-804f-d4dc2f09b16e · outbound

This paper cites Jones, and B.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Jones, and B

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:00.131786Z

Source-reported events for the cited work

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Observation d967d5c1-8a8a-437d-8e94-b7850c7a0fa3 · outbound

This paper cites PLoS Pathog, 2024.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology PLoS Pathog, 2024

Reference 25

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Source-reported events for the cited work

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Observation e394f4b6-e19b-41bf-965c-9e30867d5ce3 · outbound

This paper cites Virus Evol, 2024.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Virus Evol, 2024

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:00.097014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d16e99b4-e6dc-4194-9154-5a3efc384d15 · outbound

This paper cites AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation

Reference 27

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Observation e6352dca-a05e-4450-9d77-36615bb09f25 · outbound

This paper cites 1 edition ed.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology 1 edition ed

Reference 28

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Observation fadd19ae-9d1d-4e88-ae11-30b28a1ce9e1 · outbound

This paper cites Nature Reviews Physics, 2024.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Nature Reviews Physics, 2024

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:00.064637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9477f458-6219-46e2-a1b1-af8ae4d3057c · outbound

This paper cites Nat Hum Behav, 2024.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Nat Hum Behav, 2024

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:00.051882Z

Source-reported events for the cited work

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Observation ef9876a1-abee-4277-bc91-a2fa0ccfbf07 · outbound

This paper cites Nature Reviews Physics, 2024.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Nature Reviews Physics, 2024

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:00.038555Z

Source-reported events for the cited work

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This paper cites bioRxiv, 2025: p.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology bioRxiv, 2025: p

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:08:00.025849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0c7a12c8-1694-4a1e-94b7-0f8c32ea3251 · outbound

This paper cites Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T20:07:59.801931Z

Source-reported events for the cited work

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Observation 25255b95-9242-49de-bf29-e6704e7fdc66 · outbound

This paper cites Nature Machine Intelligence, 2024.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Nature Machine Intelligence, 2024

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:59.998287Z

Source-reported events for the cited work

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Observation 02ea2143-2d8c-47d7-b911-d824c83abf31 · outbound

This paper cites Towards an AI co-scientist.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Towards an AI co-scientist

Reference 35

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Source-reported events for the cited work

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This paper cites Generate Python code to load a CSV file, remove rows with null values, and display the first 5 rows.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Generate Python code to load a CSV file, remove rows with null values, and display the first 5 rows

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:59.969025Z

Source-reported events for the cited work

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Observation 52926969-e4f2-469e-b45e-c479028ab221 · outbound

This paper cites Create Python code using pandas and matplotlib to compute basic descriptive statistics and plot a histogram of the 'age' column.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Create Python code using pandas and matplotlib to compute basic descriptive statistics and plot a histogram of the 'age' column

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:59.958434Z

Source-reported events for the cited work

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Observation e0c27005-3ab7-4960-b381-d047d597346b · outbound

This paper cites Provide TensorFlow code to build and train a neural network on the MNIST dataset, including guidance on hyperparameter tuning.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Provide TensorFlow code to build and train a neural network on the MNIST dataset, including guidance on hyperparameter tuning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:59.948053Z

Source-reported events for the cited work

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Observation cd2925d8-b52a-4fce-8746-3f7148e3025d · outbound

This paper cites Review the following Python script and suggest improvements to optimize it for faster performance on large datasets.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Review the following Python script and suggest improvements to optimize it for faster performance on large datasets

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:59.937114Z

Source-reported events for the cited work

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This paper cites Generate a Python script for data cleaning with detailed inline comments and guidelines for Git-based version control.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Generate a Python script for data cleaning with detailed inline comments and guidelines for Git-based version control

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:59.926699Z

Source-reported events for the cited work

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Observation e886596c-9152-47ee-a8f9-9666bc7dbdb7 · outbound

This paper cites Explain the logic behind this R script in simple terms and provide an equivalent Python version for the same statistical analysis.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Explain the logic behind this R script in simple terms and provide an equivalent Python version for the same statistical analysis

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:59.915599Z

Source-reported events for the cited work

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Observation 7edba344-8abe-40ec-93ff-ebe13716b06e · outbound

This paper cites Can you write an R script to read in the dataset? B2.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Can you write an R script to read in the dataset? B2

Reference 200

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:07:59.988489Z

Source-reported events for the cited work

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Observation 5d54d385-f5c7-4967-9257-06a9a30af85a · outbound

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Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Unresolved cited work

Reference 2021

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Source-reported events for the cited work

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Observation e936a3f3-d746-4867-919d-58670d9adb82 · outbound

This paper cites an unresolved cited work.

Roadmap for using large language models (LLMs) to accelerate cross-disciplinary research with an example from computational biology Unresolved cited work

Reference 6000

Resolution: unresolved; raw_fallback, observed 2026-08-06T20:07:59.979045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.