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Paper Citation Record · LEDGER

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability

As of 24 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 1 inbound Pith citation observation for arXiv:2502.03511.

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

pith.paper-citation-record.v1
2502.03511 v1

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T04:51:24.179781Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T21:21:31.725991Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T00:16:16.039225Z

Reference resolution

64 of 64 outbound references displayed

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External citation measurements

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Outbound references

Observation 3351cf96-0f22-4d03-97db-085afec4fc3f · outbound

This paper cites NASA Systems Engineering Handbook.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability NASA Systems Engineering Handbook

Reference 1

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Observation a3f62244-2a21-4fcb-b221-a2106d083dd1 · outbound

This paper cites Larson, D.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Larson, D

Reference 2

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Observation dacc2389-8d76-4d7f-a8a3-413361b62f2b · outbound

This paper cites Systems Engineering and Analysis (5th Edition),.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Systems Engineering and Analysis (5th Edition),

Reference 3

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Observation 7ca15432-a399-4a68-8417-dc08fd4efa2c · outbound

This paper cites Architecting principles for systems-of-systems,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Architecting principles for systems-of-systems,

Reference 4

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Observation 2f5de19a-d10c-4415-806c-ce287d0a9c5d · outbound

This paper cites Mission Engineering Guide,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Mission Engineering Guide,

Reference 5

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Observation cae022f2-a1b9-46eb-a66b-a0c1c80c4de5 · outbound

This paper cites A System-of-Systems perspective for information fusion system design and evaluation,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability A System-of-Systems perspective for information fusion system design and evaluation,

Reference 6

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation b90753b0-5e2f-48d6-9c5d-32315edf0010 · outbound

This paper cites Foundational issues in engineering systems: A framing paper,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Foundational issues in engineering systems: A framing paper,

Reference 7

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Observation bde736e7-2779-4f81-aabe-69a6ce0656ab · outbound

This paper cites So You Think Your System Is Complex?: Why and How Existing Complexity Measures Rarely Agree,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability So You Think Your System Is Complex?: Why and How Existing Complexity Measures Rarely Agree,

Reference 8

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Observation 5c73dc36-a3c2-41af-979e-2887b02e3a31 · outbound

This paper cites Defense acquisitions: Assessments of selected weapon programs,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Defense acquisitions: Assessments of selected weapon programs,

Reference 9

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Observation 18e74508-a9cd-4f55-a985-1cb8795f93f7 · outbound

This paper cites NASA: Assessments of Major Projects,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability NASA: Assessments of Major Projects,

Reference 11

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Observation 23c2f497-c50d-443b-8b45-6a70a45c5d89 · outbound

This paper cites Mission Engineering and Design Using Real-Time Strategy Games: An Explainable AI Approach,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Mission Engineering and Design Using Real-Time Strategy Games: An Explainable AI Approach,

Reference 12

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Observation 7a98e29c-9d8b-41aa-93af-7af7d5e2385c · outbound

This paper cites Conceptual, Mathematical, and Analytical Foundations for Mission Engineering and System of Systems Analysis,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Conceptual, Mathematical, and Analytical Foundations for Mission Engineering and System of Systems Analysis,

Reference 13

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Observation a04512ff-b82f-4b2b-a2d2-14070a177167 · outbound

This paper cites Synthesizing Designs With Interpart Dependencies Using Hierarchical Generative Adversarial Networks,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Synthesizing Designs With Interpart Dependencies Using Hierarchical Generative Adversarial Networks,

Reference 14

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Observation 93524c34-f639-485b-abc9-b19940689cbc · outbound

This paper cites Deep Generative Models in Engineering Design: A Review,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Deep Generative Models in Engineering Design: A Review,

Reference 15

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Observation ed7ca73e-e6df-45e4-8ffa-d7b7260f38d6 · outbound

This paper cites Daphne: A Virtual Assistant for Designing Earth Observation Distributed Spacecraft Missions,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Daphne: A Virtual Assistant for Designing Earth Observation Distributed Spacecraft Missions,

Reference 16

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This paper cites Idea generation with Technology Semantic Network,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Idea generation with Technology Semantic Network,

Reference 17

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This paper cites Semantic Networks for Engineering Design: State of the Art and Future Directions,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Semantic Networks for Engineering Design: State of the Art and Future Directions,

Reference 18

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Observation 775d4af2-eddc-43a4-b05f-2d8887bba0b4 · outbound

This paper cites A commentary of GPT-3 in MIT Technology Review 2021,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability A commentary of GPT-3 in MIT Technology Review 2021,

Reference 19

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Observation 2230a54b-b757-496e-a821-07ab3889ff63 · outbound

This paper cites GPT-4 Passes the Bar Exam,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability GPT-4 Passes the Bar Exam,

Reference 20

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Observation 9a8a2ce1-7a17-4442-a7ff-6a3e64ba5485 · outbound

This paper cites ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope,

Reference 21

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This paper cites Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models,

Reference 22

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Observation 2e083e30-4263-4b6e-bb91-e5f2d5cd69c3 · outbound

This paper cites Newell and H.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Newell and H

Reference 23

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Observation a95e7241-cf65-4e09-b819-0417a9f4ac29 · outbound

This paper cites The structure of ill structured problems,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability The structure of ill structured problems,

Reference 24

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This paper cites The Architecture of Complexity,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability The Architecture of Complexity,

Reference 25

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An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Bar-yam, Dynamics Of Complex Systems

Reference 26

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This paper cites Newell and H.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Newell and H

Reference 27

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An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability GPT-3: Its Nature, Scope, Limits, and Consequences,

Reference 28

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Observation 87babe1c-d94f-4215-b964-4b7cd5aacfef · outbound

This paper cites Impact of Chat GPT on Scientific Research: Opportunities, Risks, Limitations, and Ethical 10 Issues,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Impact of Chat GPT on Scientific Research: Opportunities, Risks, Limitations, and Ethical 10 Issues,

Reference 29

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Observation 5f4257f4-b230-4b84-a814-a68dccf849d0 · outbound

This paper cites Can Large Language Models Accelerate Digital Transformation by Generating Expert-Like Systems Engineering Artifacts? Insights from an Empirical Exploration,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Can Large Language Models Accelerate Digital Transformation by Generating Expert-Like Systems Engineering Artifacts? Insights from an Empirical Exploration,

Reference 30

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Observation 6c44e1e0-f0b2-47ea-b1ce-2d2d7d6414fe · outbound

This paper cites Microfoundations of strategic problem formulation,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Microfoundations of strategic problem formulation,

Reference 31

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Observation 06d0657b-5eb7-4a67-b2ff-e6979b44f82b · outbound

This paper cites A facilitated expert-based approach to architecting ‘openable’ complex systems,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability A facilitated expert-based approach to architecting ‘openable’ complex systems,

Reference 32

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Observation ed16e0ab-46f1-4e7d-924b-beec663a06ec · outbound

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An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Space mission analysis and design,

Reference 33

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Observation d89c6833-57cd-494b-8840-0109feb8d719 · outbound

This paper cites Towards a solver-aware systems architecting framework: leveraging experts, specialists and the crowd to design innovative complex systems,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Towards a solver-aware systems architecting framework: leveraging experts, specialists and the crowd to design innovative complex systems,

Reference 34

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verified exact
doi, observed 2026-08-09T04:51:24.301486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.079431Z digest=sha256:94ef7b383eb7826d630fa6a670e36eb4ab15318ed1b9fc810f2445a06940fc3a

Observation e3c23d37-0595-4d49-a9b7-dc01ab4379a4 · outbound

This paper cites Understanding the differences between how novice and experienced designers approach design tasks,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Understanding the differences between how novice and experienced designers approach design tasks,

Reference 35

Resolution
verified exact
doi, observed 2026-08-09T04:51:24.289823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.082948Z digest=sha256:8b47741226811d4614050a7f08724e59f8917b35cbca7c252b86f49965a731d0

Observation 8f884b9d-26cd-48bd-8bdc-a4a3669eb534 · outbound

This paper cites Expertise in design: an overview,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Expertise in design: an overview,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.262348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.086456Z digest=sha256:4d88c091ede90a10d80e286957bad448decde3867efea0164594ef97871aa214

Observation b3e4c1c2-2a5a-438f-9d8a-281a914abb64 · outbound

This paper cites an unresolved cited work.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-09T04:51:26.250857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.089414Z digest=sha256:a9989202840912747af3e3617d047e056b5b707e78ad84ff0ffce55ad9c5d455

Observation 7199e643-ad60-49f1-87f2-6f72c1481a60 · outbound

This paper cites an unresolved cited work.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-09T04:51:26.240619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.093193Z digest=sha256:31a7847de1898ba57594f63d9ad732c49ae369f4c7a3a884e4eea58d9622fee8

Observation c67b86e6-2783-467e-9322-76131332255a · outbound

This paper cites Skill Gaps, Skill Shortages and Skill Mismatches: Evidence for the US,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Skill Gaps, Skill Shortages and Skill Mismatches: Evidence for the US,

Reference 39

Resolution
verified exact
doi, observed 2026-08-09T04:51:24.277721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.096966Z digest=sha256:772cd445bde87e6006e113d56d5a75a6dfaedcd8277e42766213e8eae810de8d

Observation 37c65cb3-df03-482d-b543-406020db031d · outbound

This paper cites Estimation of the workload boundary in socio-technical infrastructure management systems: The case of Belgian railroads,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Estimation of the workload boundary in socio-technical infrastructure management systems: The case of Belgian railroads,

Reference 40

Resolution
verified exact
doi, observed 2026-08-09T04:51:24.266753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.100374Z digest=sha256:d6a334bdebd3df9c9a219db5871d6f8802b4558cc5b4f09af826de7c03295aa9

Observation e191cf9e-e9c8-4888-8c03-5ae84573a7f7 · outbound

This paper cites How does agency impact human-AI collaborative design space exploration? A case study on ship design with deep generative models,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability How does agency impact human-AI collaborative design space exploration? A case study on ship design with deep generative models,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.229592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.103632Z digest=sha256:002ef42cc62fd864438b1fdba35249d84c162d387d3a8672625ba7cc1ea4ad0a

Observation 2f1c17e6-f7fd-474a-ade0-04080ea2874e · outbound

This paper cites Past Themes – RASC-AL.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Past Themes – RASC-AL

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.218750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.106553Z digest=sha256:5a1e35001d04c895e3e3c8acf60674a07d01d3c9c85febb0371ee6c83c3db9b8

Observation 8eb94c4a-5ccc-4cb6-af17-75f5c58d3b62 · outbound

This paper cites MEG-2020.pdf.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability MEG-2020.pdf

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.208422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.109929Z digest=sha256:d639e75d5666c7c7f0c7641a3bb14b022bc443debe7236f586e12523d3e431c2

Observation 90f507e4-4d39-43d2-a116-673d7aeb97bb · outbound

This paper cites Mission Engineering Integration and Interoperability (I&I),.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Mission Engineering Integration and Interoperability (I&I),

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.197208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.113151Z digest=sha256:f7bdf1a19d88ed42aa4d34c510c9455100e88b9b7f35336c782d8800316de641

Observation 8685502b-c139-41c6-8b25-790594dafc15 · outbound

This paper cites National Aeronautics and Space Act of 1958 (Unamended).

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability National Aeronautics and Space Act of 1958 (Unamended)

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.186494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.116317Z digest=sha256:43f595d4270144644fbd4e37a5a3db88b6bdb16d30f8cdc01a4207e4f3561c24

Observation a026ca8a-03c1-4296-8cb1-14cbe423ab04 · outbound

This paper cites Mission Areas and Core Capabilities | FEMA.gov.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Mission Areas and Core Capabilities | FEMA.gov

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.175470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.119605Z digest=sha256:3a45f12f2070b79f958632d97b5de7d9774a661aec342a996b4a69cdf68aac8b

Observation a145ffd1-b42a-417d-9a14-0ed386f48132 · outbound

This paper cites Mission Engineering | CISA.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Mission Engineering | CISA

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.164485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.122608Z digest=sha256:13d1e69f519b677aceca9d2ffe1f8e3b76888e8b56108e5ddbd67bf9e2c2aa96

Observation cee9489c-1ba2-4691-a31e-b16d43ac1168 · outbound

This paper cites Kossiakoff, S.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Kossiakoff, S

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.153683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.125485Z digest=sha256:b1d906710076e8c047b5d49018fabb936de255b435b8a209fc0e75739b07fbd8

Observation c9afe7da-72e5-4f9b-9725-7a96fac078cd · outbound

This paper cites A systems-theoretic articulation of stakeholder needs and system requirements,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability A systems-theoretic articulation of stakeholder needs and system requirements,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.142881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.129163Z digest=sha256:88a4f9ac716a10beacd9fff9f2ef645040a35bbdbbe1ac736375cc3879de0962

Observation 4e2a040e-0af6-443f-a6a6-03bb9dca9056 · outbound

This paper cites The concept of order of conflict in requirements engineering,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability The concept of order of conflict in requirements engineering,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.132530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.132522Z digest=sha256:c1ff4c05a673ef385788c5e62be788579bb11a8b6291cae676c3019c35258d70

Observation cad278e0-5cc7-4b0a-9e6a-fe63e901512d · outbound

This paper cites an unresolved cited work.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-09T04:51:26.122229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.136115Z digest=sha256:73e0f66fdff7e6414810f3288f0d90daab3b2f6f39ac53bdfd9e0cbe78380167

Observation 62cfa3cf-31bb-4a09-895e-ddbc57c53e2e · outbound

This paper cites On the criteria to be used in decomposing systems into modules,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability On the criteria to be used in decomposing systems into modules,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.112936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.139823Z digest=sha256:fd2faf3a86f6df2bd9d5ba0dd337ccddd0171f4ec8d63d56e9fec04a5a3fda21

Observation bbaa5ef4-d444-43e7-8d7d-6279a427171c · outbound

This paper cites The Dark Side of Modularity: How Decomposing Problems can Increase System Complexity,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability The Dark Side of Modularity: How Decomposing Problems can Increase System Complexity,

Reference 53

Resolution
verified exact
doi, observed 2026-08-09T04:51:24.254933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.142966Z digest=sha256:78c8a3e1d560b07911668dcb710b29d0a12d529c9b9e9891bad0bfaed65d72a3

Observation ad02718a-204b-410d-b99b-3dcb47f5f57f · outbound

This paper cites Change propagation analysis in complex technical systems,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Change propagation analysis in complex technical systems,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.103618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.146155Z digest=sha256:c4957f9af69e077d046d121a9fab3a60c30a133deac1c4840b70b563f6d835b6

Observation 19fa5733-26c0-48d4-ba81-be01a14120be · outbound

This paper cites A systematic review of requirements change management,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability A systematic review of requirements change management,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.090806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.149164Z digest=sha256:d1571c25566a87ed61b493719c0fafb696e30ff0261d0dd8045d3178eaaeadcd

Observation 1774ab85-57d5-472b-952f-d428622c871a · outbound

This paper cites PaDGAN: Learning to Generate High-Quality Novel Designs,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability PaDGAN: Learning to Generate High-Quality Novel Designs,

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-09T04:51:24.152261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:51:24.152261Z digest=sha256:b397fc9b871e2b9d71957936fae1c146bc607f06a113688209bb42418c7a92f3

Observation fcb2c793-f96c-4a90-8c4b-ae0bf089c3fb · outbound

This paper cites Human confidence in artificial intelligence and in themselves: The evolution and impact of confidence on adoption of AI advice,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Human confidence in artificial intelligence and in themselves: The evolution and impact of confidence on adoption of AI advice,

Reference 57

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T04:51:25.038383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.155817Z digest=sha256:2f63e4fde682ac70e119ef4c85f43f748501d9805d75877f7114254f638041f5

Observation d058a4ae-5b2b-47ae-acef-e28c00323de8 · outbound

This paper cites DesignQA: A Multimodal Benchmark for Evaluating Large Language Models' Understanding of Engineering Documentation.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability DesignQA: A Multimodal Benchmark for Evaluating Large Language Models' Understanding of Engineering Documentation

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-09T04:51:24.158748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:51:24.158748Z digest=sha256:fc1b8ef0021db9ee0bfb515ba9fc6ec81117254b1512e899ffbf94d38af4d973

Observation 7f68c1ca-1807-4222-8174-8678266a1f80 · outbound

This paper cites Knowledge cutoff date of September 2021 - ChatGPT,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Knowledge cutoff date of September 2021 - ChatGPT,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.079446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.162102Z digest=sha256:9c2c5a77ec98f64085904ad2bda702a7327b3cff5c0bd3d7293db51f7ed8f9b8

Observation a79b5768-4589-4853-b083-575c3820cfd5 · outbound

This paper cites Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future Prospects,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future Prospects,

Reference 60

Resolution
verified exact
doi, observed 2026-08-09T04:51:24.236768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.165517Z digest=sha256:a5f2fd9080cb7085c788337aafb17f0719d533b4e680ea5ac143306c71cc227d

Observation 066bb237-41f5-4a8b-a00e-f0a29d86c3f3 · outbound

This paper cites LLMMaps -- A Visual Metaphor for Stratified Evaluation of Large Language Models.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability LLMMaps -- A Visual Metaphor for Stratified Evaluation of Large Language Models

Reference 61

Resolution
verified exact
local_arxiv, observed 2026-08-09T04:51:24.224051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.168840Z digest=sha256:f9f6a9086dd18517408ebfdfdb5f76e213c5c6d39e914290fec911e619eb5d4e

Observation 46e7ae22-2f77-45b3-8497-d6585aaa332c · outbound

This paper cites GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-09T04:51:24.172520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:51:24.172520Z digest=sha256:871bc1d1f03ec11feb6cf523fc2ebfa04cf3c04668b3003c18a5b545fc235f5a

Observation b259b56b-a97f-406d-997b-6892a7f6be23 · outbound

This paper cites Assessing Large Language Models Used for Extracting Table Information from Annual Financial Reports,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Assessing Large Language Models Used for Extracting Table Information from Annual Financial Reports,

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-09T04:51:24.176322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:51:24.176322Z digest=sha256:26d95cb5916c980edac5abe7dcba896666285bd207dbe4c70dde5b7d932ff30e

Observation e8321152-c1c4-44c1-98cc-6873d30e7169 · outbound

This paper cites Do ChatGPT 4o, 4, and 3.5 Generate ‘Similar’ Ratings? Findings and Implications,.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Do ChatGPT 4o, 4, and 3.5 Generate ‘Similar’ Ratings? Findings and Implications,

Reference 64

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T04:51:24.871199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.179781Z digest=sha256:43188fa68aaca578d40104b24a147e73d2aea5922f14cac144c73b90b09c249c

Observation 3ce14061-34b0-4a06-abe1-299f77aa4304 · outbound

This paper cites Available: https://www.gao.gov/products/GAO-19-262SP.

An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability Available: https://www.gao.gov/products/GAO-19-262SP

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:51:26.311354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-09T04:51:24.003656Z digest=sha256:d6e4b3d2e4383f2321ee65eda947381c813d686d9d0b582b870131601b4142a0

Pith citing papers

Observation 25cdf90d-3dca-42ca-8111-14e1f4fe176d · inbound

Trust at Your Own Peril: A Mixed Methods Exploration of the Ability of Large Language Models to Generate Expert-Like Systems Engineering Artifacts and a Characterization of Failure Modes cites this paper.

Trust at Your Own Peril: A Mixed Methods Exploration of the Ability of Large Language Models to Generate Expert-Like Systems Engineering Artifacts and a Characterization of Failure Modes An Empirical Exploration of ChatGPT's Ability to Support Problem Formulation Tasks for Mission Engineering and a Documentation of its Performance Variability

Reference 123

Resolution
verified exact
local_arxiv, observed 2026-08-07T21:21:31.762101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-07T21:21:31.725991Z digest=sha256:6eb1d32f2da076263ac06b376011be7f35b0da04274f280b49be8f3fc449b622