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Paper Citation Record · LEDGER

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework

As of 20 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2602.18008.

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

pith.paper-citation-record.v1
2602.18008 v2

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T22:06:50.384155Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

46 of 46 outbound references displayed

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  • unresolved46
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External citation measurements

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Outbound references

Observation 7dafe06f-df77-43b9-a164-e138505ae209 · outbound

This paper cites an unresolved cited work.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Unresolved cited work

Reference 1

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Observation 48089ffd-4bbc-4da0-a179-40f4b6da0030 · outbound

This paper cites J., Marathe, M.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework J., Marathe, M

Reference 2

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Observation 93932f32-6afb-4cc2-9593-dd0760e18153 · outbound

This paper cites an unresolved cited work.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Unresolved cited work

Reference 3

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source=arxiv_source observed=2026-08-02T22:06:46.868841Z digest=sha256:5829928f539b76a42a546c1c096a844d8cae8d2db1f0f19d4e028c16b8dc8c0e

Observation a0b8e815-399f-44f1-b6e2-612e8da5ce6a · outbound

This paper cites K., Frey, C., Moh, J., Pollock, T.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework K., Frey, C., Moh, J., Pollock, T

Reference 4

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Observation 70ec26b2-50c3-4ced-948e-5968977ab302 · outbound

This paper cites Differentiable Agent-based Epidemiology.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Differentiable Agent-based Epidemiology

Reference 5

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Observation 96132d5e-2bab-4972-aca8-daf348202961 · outbound

This paper cites Y., Ray, E.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Y., Ray, E

Reference 6

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Observation 6e67337d-0acb-4b02-87a3-b3f16795305a · outbound

This paper cites R., Sifri, C.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework R., Sifri, C

Reference 7

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Observation 3e9d5c69-c05d-4856-b500-d98bf979fecd · outbound

This paper cites CALYPSO: Forecasting and Analyzing MRSA Infection Patterns with Community and Healthcare Transmission Dynamics.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework CALYPSO: Forecasting and Analyzing MRSA Infection Patterns with Community and Healthcare Transmission Dynamics

Reference 8

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Observation 7362f7aa-c34b-4f04-bb7d-b818f7a3dcda · outbound

This paper cites d., Georg, C.-P., Koziol, T., and Schasfoort, J.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework d., Georg, C.-P., Koziol, T., and Schasfoort, J

Reference 9

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Observation b1b5b51d-b3e9-4917-b5f3-aa13382987ec · outbound

This paper cites an unresolved cited work.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Unresolved cited work

Reference 10

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Observation 1cbe9488-b57f-40cb-90fc-20712c1c2622 · outbound

This paper cites The impact of social distancing, contact tracing, and case isolation interventions to suppress the covid-19 epidemic: A modeling study.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework The impact of social distancing, contact tracing, and case isolation interventions to suppress the covid-19 epidemic: A modeling study

Reference 11

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Observation 7411696c-2551-4750-8041-7ee997909c30 · outbound

This paper cites A., and Vullikanti, A.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework A., and Vullikanti, A

Reference 12

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Observation 75855522-b8dd-4276-9975-cedaa57b9366 · outbound

This paper cites and Schmidhuber, J.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework and Schmidhuber, J

Reference 13

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Observation 48aed85e-022b-4e82-8dcf-c82de346d4c3 · outbound

This paper cites Automatically learning hybrid digital twins of dynamical systems.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Automatically learning hybrid digital twins of dynamical systems

Reference 14

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Observation 458cbc30-302b-4e13-a1c9-caae377f9f9f · outbound

This paper cites Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future

Reference 15

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Observation 9777a540-2acc-46aa-bcd1-4b71fa1a6579 · outbound

This paper cites an unresolved cited work.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Unresolved cited work

Reference 16

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Observation 45cb8783-d998-4ede-8d34-a60adf62899a · outbound

This paper cites E., Kevrekidis, I.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework E., Kevrekidis, I

Reference 17

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Observation edbf35e7-952e-4b44-96dc-3addb5df3296 · outbound

This paper cites Knowledge guided machine learning: Accelerating discovery using scientific knowledge and data.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Knowledge guided machine learning: Accelerating discovery using scientific knowledge and data

Reference 18

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Observation 2068588c-3c5d-4341-b1a4-d7225c47ad32 · outbound

This paper cites Digital twins for health: a scoping review.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Digital twins for health: a scoping review

Reference 19

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Observation 47448d6c-ab3e-4403-9de2-0fe1db34058f · outbound

This paper cites F., Husch, A., Ley, C., Gon c alves, J., Skupin, A., and Magni, S.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework F., Husch, A., Ley, C., Gon c alves, J., Skupin, A., and Magni, S

Reference 20

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Observation eb6dc3f0-fd8d-4551-94d1-1f41191d619b · outbound

This paper cites O., Huynh, T., Wei, W.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework O., Huynh, T., Wei, W

Reference 21

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Observation 35f4a7a4-9d51-4867-9a58-e79392835649 · outbound

This paper cites H., Gonzalez, J., Zhang, H., and Stoica, I.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework H., Gonzalez, J., Zhang, H., and Stoica, I

Reference 22

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Observation 16305d31-c8cc-4bed-ad22-4ed07ff37dc2 · outbound

This paper cites an unresolved cited work.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Unresolved cited work

Reference 23

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Observation bd61bcf9-dec1-4eef-b14f-d08790300a8c · outbound

This paper cites and Vullikanti, A.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework and Vullikanti, A

Reference 24

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Observation 6b4e1fd7-238e-4b4c-b3cc-4c519aac571f · outbound

This paper cites Applications of digital twins in medicine.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Applications of digital twins in medicine

Reference 25

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Observation 8d231b16-cd4c-4d1a-bef3-ddd8057c02fc · outbound

This paper cites and Curtin, W.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework and Curtin, W

Reference 26

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Observation 45d4ebfb-2451-4df9-b953-125110053dad · outbound

This paper cites S., Centeno, V., Phadke, A., Poor, H.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework S., Centeno, V., Phadke, A., Poor, H

Reference 27

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Observation 12665766-b2be-45a6-99c6-24abbe3cf47d · outbound

This paper cites Foundational research gaps and future directions for digital twins.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Foundational research gaps and future directions for digital twins

Reference 28

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Observation b73dc4d7-80c1-4a55-b8b2-22db78249be7 · outbound

This paper cites A., Sacks, M.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework A., Sacks, M

Reference 29

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Observation 354c676f-0e72-4ca7-9da8-b8aa838079ca · outbound

This paper cites Epi-dnns: Epidemiological priors informed deep neural networks for modeling covid-19 dynamics.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Epi-dnns: Epidemiological priors informed deep neural networks for modeling covid-19 dynamics

Reference 30

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Observation 2af5593b-f541-491f-9920-37816a33e52b · outbound

This paper cites AlphaEvolve: A coding agent for scientific and algorithmic discovery.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework AlphaEvolve: A coding agent for scientific and algorithmic discovery

Reference 31

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Observation 40a066b9-eefc-47d1-b423-f4a24cd54d54 · outbound

This paper cites L., Barrio, R.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework L., Barrio, R

Reference 32

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Observation e258b0b4-4492-4353-af89-fba522a1f0fd · outbound

This paper cites Management strategies in a seir-type model of covid 19 community spread.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Management strategies in a seir-type model of covid 19 community spread

Reference 33

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Observation 646b1565-c7e3-46f5-877c-a658ac63165b · outbound

This paper cites Real-time influenza forecasts during the 2012--2013 season.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Real-time influenza forecasts during the 2012--2013 season

Reference 34

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Observation b3210fcb-823b-4a99-942d-68e35370cb99 · outbound

This paper cites an unresolved cited work.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Unresolved cited work

Reference 35

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Observation 933bb0d0-7a0e-4ca6-9a5e-4e67254a116e · outbound

This paper cites Y., Swarup, S., Mortveit, H., Marathe, A., Vullikanti, A., and Marathe, M.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Y., Swarup, S., Mortveit, H., Marathe, A., Vullikanti, A., and Marathe, M

Reference 36

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Observation 2163cbbd-7e84-43bf-8dee-582f3a921d4f · outbound

This paper cites N., Kaiser, ., and Polosukhin, I.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework N., Kaiser, ., and Polosukhin, I

Reference 37

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Observation b54b5496-4be2-4dd1-a849-d6bfc941f7b8 · outbound

This paper cites Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints

Reference 38

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Observation 8183602c-5b32-4ab6-823d-0cc02505685f · outbound

This paper cites C., Aleta, A., Rodrigues, F.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework C., Aleta, A., Rodrigues, F

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Observation cf87264a-0ad4-4bbb-bbd7-ed83322ce2b6 · outbound

This paper cites A general-purpose machine learning framework for predicting properties of inorganic materials.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework A general-purpose machine learning framework for predicting properties of inorganic materials

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Observation 5c80a11b-4268-4563-8fbe-e64644cd8002 · outbound

This paper cites D., Hocky, G.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework D., Hocky, G

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Observation 811cc28b-e293-41c2-85e4-4397bbba5ada · outbound

This paper cites Inference of seasonal and pandemic influenza transmission dynamics.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Inference of seasonal and pandemic influenza transmission dynamics

Reference 42

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Observation 4d5bbb33-7622-4c8f-b901-c23c415d4923 · outbound

This paper cites and Curtin, W.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework and Curtin, W

Reference 43

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Observation ef7743ce-3aca-44e0-98be-f9b44174ccce · outbound

This paper cites A survey on agent workflow--status and future.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework A survey on agent workflow--status and future

Reference 44

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Observation 1077b9de-8df2-4f99-ae4a-cd97d66a80eb · outbound

This paper cites Large language models to accelerate organic chemistry synthesis.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework Large language models to accelerate organic chemistry synthesis

Reference 45

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Observation 34ad6201-be84-45bd-bc88-b6f48a082361 · outbound

This paper cites write newline.

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework write newline

Reference 46

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