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Paper Citation Record · LEDGER

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System

As of 8 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2607.13608.

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

pith.paper-citation-record.v1
2607.13608 v1

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T04:44:28.756555Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

63 of 63 outbound references displayed

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External citation measurements

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Outbound references

Observation 66f5da3b-6c04-4528-be10-91d11574084e · outbound

This paper cites an unresolved cited work.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 1

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Observation 6fc80c5a-e50f-4ca4-a4db-d4744a60683c · outbound

This paper cites an unresolved cited work.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 2

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Observation d727a3bf-fd89-4c6e-b189-da2e3f88ff2f · outbound

This paper cites an unresolved cited work.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 3

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Observation 118b1aac-9ac3-4281-b1e0-ba7d99f1d8da · outbound

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 4

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This paper cites Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems

Reference 5

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Observation 28f5ef00-e9b8-4168-ba76-17ad72490838 · outbound

This paper cites an unresolved cited work.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 6

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This paper cites an unresolved cited work.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 7

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Observation eb291d52-30d3-44b1-a765-43bd5fbb8000 · outbound

This paper cites A., Mahmud, A.et al.Exploring the role of large language models in the scientific method: From hypothesis to discovery.npj Artificial Intelligence1, 14 (2025).

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System A., Mahmud, A.et al.Exploring the role of large language models in the scientific method: From hypothesis to discovery.npj Artificial Intelligence1, 14 (2025)

Reference 8

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Observation e6ea12f6-ef7b-40b7-8e8a-ba8237beadf8 · outbound

This paper cites & Clune, J.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Clune, J

Reference 9

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Ulrich, K

Reference 10

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This paper cites & Clune, J.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Clune, J

Reference 11

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 12

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Observation e616305f-e134-443a-bb38-265eb1f3f50c · outbound

This paper cites & Crockett, M.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Crockett, M

Reference 13

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Observation 151bce26-1f7b-4c6b-8a39-0f217d87248a · outbound

This paper cites Ai research assistants are changing science.Nature651, 853 (2026).

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Ai research assistants are changing science.Nature651, 853 (2026)

Reference 14

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This paper cites The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Reference 15

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Observation 4008665f-b70b-4f62-a457-3982a966bd66 · outbound

This paper cites Agent Laboratory: Using LLM Agents as Research Assistants.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Agent Laboratory: Using LLM Agents as Research Assistants

Reference 16

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Observation 146bac97-f979-4dfc-9a34-7c4a05700704 · outbound

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 17

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Observation 61842e32-3735-4e16-be36-51ccaf489ddc · outbound

This paper cites PaperOrchestra: A Multi-Agent Framework for Automated AI Research Paper Writing.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System PaperOrchestra: A Multi-Agent Framework for Automated AI Research Paper Writing

Reference 18

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Observation 716532a5-f59d-41c1-9832-9701208cb9b1 · outbound

This paper cites LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models

Reference 19

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Observation f0fde375-77cf-4c28-816a-83215513f1e5 · outbound

This paper cites Z., Georgievska, A.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Z., Georgievska, A

Reference 20

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This paper cites R., Lober, L., Previdelli, I.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System R., Lober, L., Previdelli, I

Reference 21

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Observation 5108484b-d59b-4269-bb6d-1d47841309d2 · outbound

This paper cites When AI Co-Scientists Fail: SPOT-a Benchmark for Automated Verification of Scientific Research.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System When AI Co-Scientists Fail: SPOT-a Benchmark for Automated Verification of Scientific Research

Reference 22

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This paper cites Nature Machine Intelligence1–14 (2026).

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Nature Machine Intelligence1–14 (2026)

Reference 23

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This paper cites & Reviriego, P.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Reviriego, P

Reference 24

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Treutlein, B

Reference 25

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This paper cites M., Shivnaraine, R.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System M., Shivnaraine, R

Reference 26

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 28

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Marchetti, L

Reference 29

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Radulescu, O

Reference 30

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Observation ea3f1a21-3ac7-4afe-90f9-194ab2a1833c · outbound

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 31

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Chawla, S

Reference 32

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Lipson, H

Reference 33

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 34

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System E., Atiku, S

Reference 35

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Reuter, K

Reference 36

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 37

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Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 38

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Observation cf9f5ac3-cbd7-40df-b0fe-58cf2b81536a · outbound

This paper cites Frontiers in Ecology and Evolution8, 530135 (2020).

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Frontiers in Ecology and Evolution8, 530135 (2020)

Reference 39

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Observation c31fef47-7161-43b1-bb75-0a4cff2db451 · outbound

This paper cites & Lazebnik, T.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Lazebnik, T

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source=pdf_text observed=2026-08-02T04:44:27.105875Z digest=sha256:00f5d6d0170c3ccedc7f5bcc043a58ba50bfe406e39a473d5bd511d9c32b2974

Observation 8428facd-d666-4491-92cc-47a872f358ed · outbound

This paper cites L., Proctor, J.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System L., Proctor, J

Reference 41

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source=pdf_text observed=2026-08-02T04:44:27.208581Z digest=sha256:7ccbb931057fef1c45eaab6f58decee85be7a50466e47c309ad51b97680e42d0

Observation cdcaf5fc-5ca2-47a9-8811-11af8088b520 · outbound

This paper cites & Dˇ zeroski, S.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Dˇ zeroski, S

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source=pdf_text observed=2026-08-02T04:44:27.309577Z digest=sha256:f11840a291f109de4963a2f0b9e1febee7fc5771213584fac115109d5bead5a6

Observation 28a7e799-33b2-429d-97e4-a046df170198 · outbound

This paper cites an unresolved cited work.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 43

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source=pdf_text observed=2026-08-02T04:44:27.372314Z digest=sha256:ceb2706a35bb96a0a37cab48cb84e8e9b04cbabd72633b641760876f9db1da50

Observation 14f9ba24-efe3-4301-99a8-0707566d9489 · outbound

This paper cites & Lazebnik, T.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Lazebnik, T

Reference 44

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source=pdf_text observed=2026-08-02T04:44:27.449883Z digest=sha256:cf535f6bfe96f8df6c16d2ceb3798a2084b36c53eaf580ef41a00f3776c4774b

Observation a18b4ef3-33e2-424a-ae36-14bcbd6dc4d0 · outbound

This paper cites & Lazebnik, T.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Lazebnik, T

Reference 45

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source=pdf_text observed=2026-08-02T04:44:27.491847Z digest=sha256:0b89f5fd462cf6fc35b2cece57bbdaec9c3d2a32aa351cd33da53f23c3a185f6

Observation bdc8dfe5-72fe-4ef0-b31c-6b824ca9aa1f · outbound

This paper cites & Shen, L.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Shen, L

Reference 46

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source=pdf_text observed=2026-08-02T04:44:27.579498Z digest=sha256:817ebfc1159ba56f8ac3517c7fb92ac36db9ced3c456588bb9d6b0e8546e6b29

Observation c0674bdc-a800-428b-adad-9d0649597da3 · outbound

This paper cites & Tegmark, M.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Tegmark, M

Reference 47

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source=pdf_text observed=2026-08-02T04:44:27.653743Z digest=sha256:b174bfb200ca27565e510ee144141b6fb14a7ce66676ddd659d5afa4ac313bc5

Observation 40a1d1ec-6192-42a2-ae35-38beda2a6e4d · outbound

This paper cites & Babuˇ ska, R.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Babuˇ ska, R

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source=pdf_text observed=2026-08-02T04:44:27.731756Z digest=sha256:395c1e30437bb87dca0b6c996c0df7c00baf796016a020c8b5d6165244d51ba5

Observation f7312b27-da4e-4544-a59d-b8295bbb6e87 · outbound

This paper cites & Wang, Z.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Wang, Z

Reference 49

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source=pdf_text observed=2026-08-02T04:44:27.843578Z digest=sha256:2e964631a8d0f934d20ca3b309053a55b7e5999cec87558d811defca09fbd3a0

Observation 94d8e53b-0133-4768-9503-57c421083dc4 · outbound

This paper cites O., Burlacu, B., Haider, C.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System O., Burlacu, B., Haider, C

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source=pdf_text observed=2026-08-02T04:44:27.957192Z digest=sha256:be994031263b4de7e5c38fa36edd5b86a440d7828ae8c56d2bccccc4a236e619

Observation f0e51863-0b7f-4737-b977-83b6e1a74a56 · outbound

This paper cites D., Nacion, F.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System D., Nacion, F

Reference 51

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source=pdf_text observed=2026-08-02T04:44:28.065055Z digest=sha256:2f75b8c793d8374880a9e1502e6381cdd67c84ac4d53d39bea9226733adcfd00

Observation 24e928cf-a427-4506-ba8c-03ccecbd1cb0 · outbound

This paper cites InGenetic programming theory and practice XVII, 79–99 (Springer, 2020).

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System InGenetic programming theory and practice XVII, 79–99 (Springer, 2020)

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source=pdf_text observed=2026-08-02T04:44:28.157887Z digest=sha256:432c0322db5c673c8591b560ea4191886f1d6eb54bb8a66e9861e6f01cd006e2

Observation 692cd75e-1b20-484a-9752-33bdf08874f6 · outbound

This paper cites A.et al.Delay differential equations and applications to biology (2021).

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System A.et al.Delay differential equations and applications to biology (2021)

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source=pdf_text observed=2026-08-02T04:44:28.217536Z digest=sha256:dbf8a3bad5ed242da461e9170cffb4a27a04ad74201bb63c9819cafaa0cb07de

Observation 8d8ec749-a12e-4afc-8e93-f1b84d56da56 · outbound

This paper cites & Rotariu, M.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Rotariu, M

Reference 54

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source=pdf_text observed=2026-08-02T04:44:28.265589Z digest=sha256:9058f84e24f11bb8cd867e5b80a64dee96f3a1f425f319cba08f775e5ef0e9ec

Observation 3f34872a-ddcf-4f1f-abc9-d73a7ca53cf9 · outbound

This paper cites & Wedelin, D.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Wedelin, D

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source=pdf_text observed=2026-08-02T04:44:28.305116Z digest=sha256:c8b7d598a2a1576b63857c6664e1a408eab71bd9a297ac3bfb8e08fdfe58faa8

Observation f21ab72a-1d4d-4fbd-a107-fa86522dbafe · outbound

This paper cites & MacLean, A.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & MacLean, A

Reference 56

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source=pdf_text observed=2026-08-02T04:44:28.353627Z digest=sha256:82c89f0862ba2e010257cc605d0aa98b0aa1843f4d8049f2ca6aa1efc93a48e0

Observation 20918d77-96ec-4870-bf72-5281f6c942b4 · outbound

This paper cites & Carvalho, R.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System & Carvalho, R

Reference 57

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source=pdf_text observed=2026-08-02T04:44:28.393545Z digest=sha256:27657f96040b67de1065fd7626d5f27168ae63cc3090a69a23346dd716113b78

Observation cf4a0814-b026-4b6e-8463-35883dd84c15 · outbound

This paper cites an unresolved cited work.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 58

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source=pdf_text observed=2026-08-02T04:44:28.441717Z digest=sha256:24bff496e25ea3b106fb1be0c3be1f6319fdda232c8d40cfb960a9075a362342

Observation cce12a77-ac85-42dc-86bf-d55395e2825b · outbound

This paper cites L., Proctor, J.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System L., Proctor, J

Reference 59

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source=pdf_text observed=2026-08-02T04:44:28.479138Z digest=sha256:a87365d82aff0d80f7ff642c4e70b9d1b85aa25ff21e3bcb4ca90d2a926f749e

Observation cade3970-7e02-469b-bd05-d4b7adfabcaa · outbound

This paper cites N.et al.Universally sloppy parameter sensitivities in systems biology models.PLOS Computational Biology3, e189 (2007).

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System N.et al.Universally sloppy parameter sensitivities in systems biology models.PLOS Computational Biology3, e189 (2007)

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source=pdf_text observed=2026-08-02T04:44:28.608866Z digest=sha256:d65269752017136bb4a62dd760a58d4085a15ae9bc3806669594233dfc23083e

Observation a1d5d1ce-9d06-49d0-9c9f-f6777b36362b · outbound

This paper cites an unresolved cited work.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 61

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source=pdf_text observed=2026-08-02T04:44:28.645626Z digest=sha256:8c34826f0a594a41c526baac37e39b3952a231914da5e1f5317655fe04b50ee4

Observation d7d59d28-6caa-4eb0-b135-24513c926254 · outbound

This paper cites an unresolved cited work.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Unresolved cited work

Reference 62

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source=pdf_text observed=2026-08-02T04:44:28.692347Z digest=sha256:a00f713387a3e27158c82cb5448bf9b0493bae2cb367db51f285a958ee27c6d2

Observation f1b00df9-22ad-41a2-ac1d-7f496b17b8fe · outbound

This paper cites Universal Differential Equations for Scientific Machine Learning.

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System Universal Differential Equations for Scientific Machine Learning

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source=pdf_text observed=2026-08-02T04:44:28.756555Z digest=sha256:cc61f82dd933924bc5032f9edfe7a250024f2c12aad7693f5c323afad4273b92

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