Paper Citation Record · LEDGER

Utilizing AI for Aviation Post-Accident Analysis Classification

As of 14 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2506.00169.

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

pith.paper-citation-record.v1
2506.00169 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:14:44.786109Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

29 of 29 outbound references displayed

verified exact4
verified fuzzy20
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 99298101-e6f6-4c64-ae0c-0da9b5ec7d57 · outbound

This paper cites Urban Aviation: The Future Aerospace Transportation System for Intercity and Intracity Mobility,.

Utilizing AI for Aviation Post-Accident Analysis Classification Urban Aviation: The Future Aerospace Transportation System for Intercity and Intracity Mobility,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T12:14:41.132009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c8221f9-f569-40ec-a354-bbd8f033bca0 · outbound

This paper cites Urban Air Mobility Airspace Integration Concepts and Considerations,.

Utilizing AI for Aviation Post-Accident Analysis Classification Urban Air Mobility Airspace Integration Concepts and Considerations,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:50.270528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5d90c129-7c18-4cfe-b293-3582a70050a5 · outbound

This paper cites A Concept of Operations (ConOps) of an In-time Aviation Safety Management System (IASMS) for Advanced Air Mobility (AAM),.

Utilizing AI for Aviation Post-Accident Analysis Classification A Concept of Operations (ConOps) of an In-time Aviation Safety Management System (IASMS) for Advanced Air Mobility (AAM),

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:50.067902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 21771c05-0220-45a3-ae1e-16fe88d02281 · outbound

This paper cites The Regulatory Framework for Safety Management Systems in Airworthiness Organisations,.

Utilizing AI for Aviation Post-Accident Analysis Classification The Regulatory Framework for Safety Management Systems in Airworthiness Organisations,

Reference 4

Resolution: verified exact; doi, observed 2026-08-07T12:14:45.794501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b84035b0-5b91-4cf7-a0c8-20c99da21fb9 · outbound

This paper cites An artificial intelligence approach to onboard fault monitoring and diagnosis for aircraft applications,.

Utilizing AI for Aviation Post-Accident Analysis Classification An artificial intelligence approach to onboard fault monitoring and diagnosis for aircraft applications,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:49.832438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f0d9b31a-577d-4898-af07-383d82974af3 · outbound

This paper cites Intelligent Decision Aiding in the Flight Deck: An Integration of Artificial Intelligence and Human Factors Research,.

Utilizing AI for Aviation Post-Accident Analysis Classification Intelligent Decision Aiding in the Flight Deck: An Integration of Artificial Intelligence and Human Factors Research,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:49.676152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d73db7be-7ced-4fdf-963b-dce458500277 · outbound

This paper cites Machine Learning for Air Transport Planning and Management,.

Utilizing AI for Aviation Post-Accident Analysis Classification Machine Learning for Air Transport Planning and Management,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:49.543619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 668c43e2-e7b7-4287-92d5-f49227a67782 · outbound

This paper cites Sequential Classification of Aviation Safety Occurrences with Natural Language Processing,.

Utilizing AI for Aviation Post-Accident Analysis Classification Sequential Classification of Aviation Safety Occurrences with Natural Language Processing,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:49.224075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 494343ca-8657-4649-81d9-d30df6d6808c · outbound

This paper cites Aviation - BERT: A Preliminary Aviation-Specific Natural Language Model,.

Utilizing AI for Aviation Post-Accident Analysis Classification Aviation - BERT: A Preliminary Aviation-Specific Natural Language Model,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:48.951692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2ff5949f-501d-40d6-9d23-fa40827f2518 · outbound

This paper cites SafeAeroBERT: Towards a Safety -Informed Aerospace -Specific Language Model,.

Utilizing AI for Aviation Post-Accident Analysis Classification SafeAeroBERT: Towards a Safety -Informed Aerospace -Specific Language Model,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:48.601077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation be38d082-d408-4c8b-876b-7dfc0e90103f · outbound

This paper cites BERT for Aviation Text Classification,.

Utilizing AI for Aviation Post-Accident Analysis Classification BERT for Aviation Text Classification,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:48.388662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2c879151-fc93-44ed-abc3-c96cdd1f7d91 · outbound

This paper cites Airbus A32x Versus Boeing 737 Safety Occurrences,.

Utilizing AI for Aviation Post-Accident Analysis Classification Airbus A32x Versus Boeing 737 Safety Occurrences,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:14:42.297224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39990f0d-9376-4b22-abd9-a194951708e2 · outbound

This paper cites Visual Flight into Instrument Meteorological Condition: A Post Accident Analysis,.

Utilizing AI for Aviation Post-Accident Analysis Classification Visual Flight into Instrument Meteorological Condition: A Post Accident Analysis,

Reference 13

Resolution: verified exact; doi, observed 2026-08-07T12:14:45.548280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0a3c2112-13b6-44d3-9d38-b4bf9db57d40 · outbound

This paper cites Classification and analysis of errors reported in aircraft maintenance manuals,.

Utilizing AI for Aviation Post-Accident Analysis Classification Classification and analysis of errors reported in aircraft maintenance manuals,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:48.142537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c628926b-b376-4942-a07f-3dab05b54864 · outbound

This paper cites Topic Modeling Analysis of Aviation Accident Reports: A Comparative Study between LDA and NMF Models,.

Utilizing AI for Aviation Post-Accident Analysis Classification Topic Modeling Analysis of Aviation Accident Reports: A Comparative Study between LDA and NMF Models,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:47.965574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 296aa4ef-8522-4b5e-a680-4e9b98d5625e · outbound

This paper cites Artificial Intelligence in Aviation Safety: Systematic Review and Biometric Analysis,.

Utilizing AI for Aviation Post-Accident Analysis Classification Artificial Intelligence in Aviation Safety: Systematic Review and Biometric Analysis,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:14:42.832557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddbf7347-183e-4e29-86af-a3a6af95b53e · outbound

This paper cites Natural Language Processing (NLP) in Aviation Safety: Systematic Review of Research and Outlook into the Future,.

Utilizing AI for Aviation Post-Accident Analysis Classification Natural Language Processing (NLP) in Aviation Safety: Systematic Review of Research and Outlook into the Future,

Reference 17

Resolution: verified exact; doi, observed 2026-08-07T12:14:45.305600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 84011193-7a0f-4767-88e0-cf2f4a250afa · outbound

This paper cites Examining the Potential of Generative Language Models for Aviation Safety Analysis: Case Study and Insights Using the Aviation Safety Reporting System (ASRS),.

Utilizing AI for Aviation Post-Accident Analysis Classification Examining the Potential of Generative Language Models for Aviation Safety Analysis: Case Study and Insights Using the Aviation Safety Reporting System (ASRS),

Reference 18

Resolution: verified exact; doi, observed 2026-08-07T12:14:45.012338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 209b68a9-1078-4111-af43-e552869ed571 · outbound

This paper cites Comparative Study of Deep Learning Architectures for Textual Damage Level Classification,.

Utilizing AI for Aviation Post-Accident Analysis Classification Comparative Study of Deep Learning Architectures for Textual Damage Level Classification,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:47.753321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 413da59f-6e3d-4f95-a122-01deb52b980a · outbound

This paper cites Natural Language Processing and Deep Learning Models to Classify Phase of Flight in Aviation Safety Occurrences,.

Utilizing AI for Aviation Post-Accident Analysis Classification Natural Language Processing and Deep Learning Models to Classify Phase of Flight in Aviation Safety Occurrences,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:47.547540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8fedce01-cfc0-4c20-8bb7-5f84d06b35e6 · outbound

This paper cites Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports,.

Utilizing AI for Aviation Post-Accident Analysis Classification Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:47.407708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8d9df2eb-a1a1-449c-87a6-eb00fdfce439 · outbound

This paper cites Phase of Flight Classification in Aviation Safety Using LSTM, GRU, and BiLSTM: A Case Study with ASN Dataset,.

Utilizing AI for Aviation Post-Accident Analysis Classification Phase of Flight Classification in Aviation Safety Using LSTM, GRU, and BiLSTM: A Case Study with ASN Dataset,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:47.244601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b720a2fb-3baf-4806-a8d9-0cded5913b30 · outbound

This paper cites Impact of Dataset Size & Data Source on Aviation Safety Incident Prediction Models with Natural Language Processing,.

Utilizing AI for Aviation Post-Accident Analysis Classification Impact of Dataset Size & Data Source on Aviation Safety Incident Prediction Models with Natural Language Processing,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:46.970156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cfd50156-9d49-475d-9ad6-395e5b7bdd03 · outbound

This paper cites Comparative Analysis of Topic Modeling Techniques on ATSB Text Narratives Using Natural Language Processing,.

Utilizing AI for Aviation Post-Accident Analysis Classification Comparative Analysis of Topic Modeling Techniques on ATSB Text Narratives Using Natural Language Processing,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:46.692403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1279f68a-6d47-47ed-b622-fe9e0581f750 · outbound

This paper cites Exploring Aviation Incident Narratives Using Topic Modeling and Clustering Techniques,.

Utilizing AI for Aviation Post-Accident Analysis Classification Exploring Aviation Incident Narratives Using Topic Modeling and Clustering Techniques,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:46.413437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e3c23869-768d-4466-ab42-b267ff4835e5 · outbound

This paper cites Applications of natural language processing in aviation safety: A review and qualitative analysis,.

Utilizing AI for Aviation Post-Accident Analysis Classification Applications of natural language processing in aviation safety: A review and qualitative analysis,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:46.278424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 42b93ed2-1c8c-4fa8-9c1d-8f32d4bfd2e5 · outbound

This paper cites A Survey Protocol to Assess Meaningfulness and Usefulness of Automated Topic Finding in the NASA Aviation Safety Reporting System,.

Utilizing AI for Aviation Post-Accident Analysis Classification A Survey Protocol to Assess Meaningfulness and Usefulness of Automated Topic Finding in the NASA Aviation Safety Reporting System,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:14:46.116355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2e5f7784-4280-4371-9aae-84facf41f05c · outbound

This paper cites Sequential deep learning from NTSB reports for aviation safety prognosis,.

Utilizing AI for Aviation Post-Accident Analysis Classification Sequential deep learning from NTSB reports for aviation safety prognosis,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T12:14:44.577676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ce8a93a-fffb-41a8-bc9f-65c0cf74a060 · outbound

This paper cites A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications,.

Utilizing AI for Aviation Post-Accident Analysis Classification A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:14:44.786109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.